# Data Science UA Data Science UA Reviews (14), Pricing, Services & Verified Ratings - 4.9 out of 5 average review rating - 0 connections joined Data Science UA's Network [Visit Website](https://data-science-ua.com/) [Get a Custom Proposal](https://clutch.co/profile/data-science-ua) **Drive business growth with proven AI expertise** Data Science UA brings 9+ years of applied experience and a team of 80+ mature AI experts into the competition for companies that strive to move faster, work smarter, and achieve next-level business success! **What sets us apart?** With a strong portfolio of 200+ custom AI projects, we serve clients in 20+ countries, bringing together deep technical skills and business know-how. Whether it's AI agent-powered workflows or custom LLM systems, we deliver proven results. Our experts speak both the language of tech and business to develop AI that ideally fits your needs, smoothly integrates with your systems, and gets adopted by your teams in no time. **Our core services** - Custom AI development - Comprehensive AI consulting - Global tech talent recruitment - Corporate AI training for tech and business teams **The benefits our clients get** - Actionable AI solutions built for real-world applications - Expert hiring and scalable team building - Unparalleled knowledge and delivery speed - Transparent collaboration and pricing models **Want AI to bring measurable results without wasting resources?** Data Science UA offers a transparent and straightforward approach for not-so-simple solutions. That's how we make AI work for you! ## Company Information - Minimum project size: $10,000+ - Hourly rate: $25 - $49 - Number of employees: 50 - 249 - 2 Locations: - London, England (Headquarters) - Zürich, Switzerland - Founded in 2016 ## Services, Focus Areas, Industries, and Clients ### Service Lines - 25% AI Development - 25% IT Staff Augmentation - 20% AI Agents - 20% AI Consulting - 5% Corporate Training & Coaching - 5% Data Annotation Services ### Focus Areas - AI Consulting Focus: - 50% AI Deployment - 30% AI Strategy - 15% AI Security Management - 5% AI Maturation - AI Agent Development Focus: - 40% AI Agent Frameworks - 30% AI Agent Platforms & Builders - 30% Voice AI Agents - AI Technologies & Models: - 40% Open AI GPT-3 - 20% Deepmind Gopher - 20% Hugging Face Bloom - 10% Anthropic - 10% Codegeex - Corporate Training & Coaching Focus: - 40% Workforce Resiliency Training - 35% Project Management Training - 25% Cybersecurity Awareness Training - AI Expertise: - 35% Machine Learning - 25% Computer Vision - 20% Natural Language Processing - 10% AI Recommendation Systems - 10% Chatbots & Conversational AI - AI Platform Integration Focus: - 30% Salesforce AI Integration - 25% Google Workspace AI Integration - 25% Hubspot AI Integration - 20% Wix AI Integration - Data Annotation Media: - 25% Audio Annotation - 25% Image Annotation - 25% Text Annotation - 25% Video Annotation - AI Agent Purpose Focus: - 20% Customer Service AI Agents - 20% Productivity AI Agents - 20% Workflow AI Agents - 15% Data Analysis AI Agents - 10% Coding & Development AI Agents - 10% Software Testing AI Agents - 5% Sales & Lead Generation AI Agents ### Industries - 20% eCommerce - 25% Financial services - 20% Manufacturing - 15% Energy & natural resources - 20% Retail ### Clients - 50% Small Business (<$10M) - 50% Midmarket ($10M - $1B) ## Pricing Snapshot Average rating for cost based on this provider's reviews: 4.9 out of 5 **What Clients Have Said** *(This summary is based on verified Clutch reviews.)*: Data Science UA offers competitive pricing and good value for cost, as noted by multiple clients. Their services range from AI solutions to recruitment, with projects managed efficiently. Clients appreciate their clear communication and timely delivery, aligning well with budget expectations. **Most Common Project Size**: $10,000 to $49,000 based on 13 reviews *(Pricing information for this provider is based on reviews where the project size was available.)* ### Pricing by Service - Custom Software Development: $10,000 to $49,000 based on 3 reviews - AI Development: $50,000 to $199,999 based on 3 reviews - HR Consulting: $10,000 to $49,000 based on 3 reviews - Recruiting: Less than $10,000 based on 3 reviews - AI Consulting: $50,000 to $199,999 based on 1 review - BI & Big Data Consulting & SI: $10,000 to $49,000 based on 1 review - Branding: Less than $10,000 based on 1 review - Cloud Consulting & SI: $10,000 to $49,000 based on 1 review - IoT Development: $50,000 to $199,999 based on 1 review - Product Marketing: Less than $10,000 based on 1 review - IT Staff Augmentation: $50,000 to $199,999 based on 1 review - Direct Marketing: Less than $10,000 based on 1 review ## Reviews Clutch investigates each reviewer's identity and work history. Every review goes through a rigorous, human-led verification process to confirm the reviewer's identity, and reviews that we verify are visibly marked as 'Verified' so you can trust that they come from a real client. [Learn More](https://help.clutch.co/en/knowledge/how-clutch-verifies-reviews) ### Data Science UA Review Insights Overall Review Rating: 4.9 - Quality: 4.9 - Schedule: 5.0 - Cost: 4.9 - Willing to Refer: 5.0 ### Top Mentions - Communicative (6 mentions) - Great project management (5 mentions) - Timely (5 mentions) - Unique expertise (4 mentions) - Great team (2 mentions) - High-quality work (2 mentions) - Professional (2 mentions) - Understands their clients' needs (2 mentions) - Collaborative (1 mentions) - Creative (1 mentions) - Detail-oriented (1 mentions) - Exceptional performance (1 mentions) - Flexible (1 mentions) - Honest (1 mentions) - Proactive (1 mentions) - Translate ideas into products (1 mentions) ### Review Highlights **Comprehensive Educational Services** Data Science UA's educational projects have been successful, with over 2,000 attendees. Their end-to-end management of educational courses is highly regarded, showcasing their expertise in data science and AI. **Proactive and Persistent Talent Search** The team was commended for their persistence in finding candidates that met high standards, even when the process was challenging. Their proactive search efforts resulted in finding ideal fits for clients. **Impressive Technical and Soft Skills** Clients were impressed by Data Science UA's combination of technical prowess and strong soft skills. Their ability to deliver creative solutions and maintain excellent communication was noted as a key strength. **Effective Recruitment Services** Clients praised Data Science UA's recruitment services for identifying and onboarding skilled AI and ML engineers. They appreciated the team's understanding of technical requirements and cultural fit, which led to successful hires. **Minor Presentation Improvements Suggested** While overall feedback was positive, one client suggested minor improvements in the presentation and delivery of final reports. However, this did not overshadow the team's exceptional performance. **Rising Above Geopolitical Challenges** Despite geopolitical challenges impacting travel, clients remain satisfied with the remote collaboration and management provided by Data Science UA, highlighting their resilience and adaptability. **Exceptional Communication and Client Orientation** Clients consistently highlighted Data Science UA's strong communication skills and client-focused approach. Their ability to understand business needs and maintain transparent communication was highly valued. **Proficient in AI-Powered Solutions** Data Science UA excels in delivering AI-powered solutions like image recognition systems. Clients noted significant improvements in automation, accuracy, and integration, reducing manual efforts and enhancing search functionalities. **Successful Recruitment for Diverse Industries** Data Science UA successfully recruited talent across various industries, including fintech, e-commerce, and health-tech. They are adept at finding candidates that align with both technical and cultural requirements. ### Data Science UA Reviews #### Custom Software & API Dev for IT Company **The Project** - Services: AI Consulting, AI Development, Custom Software Development - Project size: $50,000 to $199,999 - Project length: Aug. - Nov. 2023 **Project Summary**: Data Science UA built a computer vision (CV) model for an IT company. The model needed to detect and categorize objects in images, extract metadata, and integrate into the client's existing system with an API. **Review Rating**: 5.0 - Quality: 5.0 - Schedule: 5.0 - Cost: 5.0 - Willing to Refer: 5.0 **The Reviewer** Department Director, WEZOM - Industry: Information technology - Client size: 201-500 Employees - Review Type: Online Review - Verified **The Review** — Feb 17, 2025 **Feedback Summary**: Data Science UA's CV model helped the client reduce manual image review efforts, improve object detection accuracy, and accelerate image search functionality. The team managed the project well, responded quickly to questions, and provided regular updates. Their client-oriented approach stood out. ""They ensured the project stayed on track and met all our expectations."" **BACKGROUND** Please describe your company and position.I am a department director at of WEZOMDescribe what your company does in a single sentence.WEZOM specializes in providing custom IT & Digital solutions, transforming B2B, B2C, and D2C businesses with advanced IT-ecosystems. **OPPORTUNITY / CHALLENGE** What specific goals or objectives did you hire Data Science UA to accomplish?We needed an AI-powered solution that could automate the processes of image categorization and metadata tagging. It would ensure faster, more accurate results while reducing our team’s reliance on manual effort. **SOLUTION** How did you find Data Science UA?Online SearchWhy did you select Data Science UA over others?Close to my geographic locationPricing fit our budgetGreat culture fitHow many teammates from Data Science UA were assigned to this project?2-5 EmployeesDescribe the scope of work in detail. Please include a summary of key deliverables. They worked closely with us to understand our requirements and designed a CV model that could detect and categorize objects in images with high accuracy, extract metadata automatically, and integrate into our existing system with a secure API.Everything from data collection to model deployment was on them. **RESULTS & FEEDBACK** What were the measurable outcomes from the project that demonstrate progress or success? Their AI-powered image recognition system helped to reduce our manual image review efforts. It significantly improved accuracy in object detection and data searchability with metadata extraction.We experienced much faster image search functionality. It was also quite easy for our development team to deploy it.Describe their project management. Did they deliver items on time? How did they respond to your needs? The project was managed exceptionally well. We got regular progress updates via weekly meetings. They were quick to respond to our questions.They additionally provided us with transparent documentation for all AI model components.What was your primary form of communication with Data Science UA?Email or Messaging AppWhat did you find most impressive or unique about this company? Data Science UA has great ability to understand business needs and requirements and translate them into practical AI technology.  Their team was highly communicative and client-oriented, they ensured the project stayed on track and met all our expectations.Are there any areas for improvement or something Data Science UA could have done differently?While the initial model deployment went smoothly, we  --- #### Recruitment Services for Software Dev Company **The Project** - Services: AI Development, IT Staff Augmentation, Recruiting - Project size: $50,000 to $199,999 - Project length: Dec. 2022 - May 2023 **Project Summary**: A software development company hired Data Science UA to recruit a team of AI engineers to develop a chatbot using AI. Within six months, the team found qualified candidates and led a smooth onboarding process. **Review Rating**: 5.0 - Quality: 5.0 - Schedule: 5.0 - Cost: 5.0 - Willing to Refer: 5.0 **The Reviewer** CEO, 8allocate - Industry: Other industries - Client size: 51-200 Employees - Review Type: Online Review - Verified **The Review** — Sep 25, 2023 **Feedback Summary**: Data Science UA onboarded AI engineers who blended effortlessly into the client’s internal team. The new engineers appreciated the recruitment team's honesty throughout the whole process. They had an excellent ability to identify the right candidates, and the client was pleased with the results. ""Data Science UA's project management style was impeccable."" **BACKGROUND** Please describe your company and position.I am the CEO of 8allocateDescribe what your company does in a single sentence.With our HQ in Estonia and development centers in Poland, Ukraine, and Latin America, we offer custom and innovative solutions in various industries focusing on FinTech and EdTech worldwide. **OPPORTUNITY / CHALLENGE** What specific goals or objectives did you hire Data Science UA to accomplish?Hire experienced AI engineers **SOLUTION** How did you find Data Science UA?ReferralWhy did you select Data Science UA over others?Close to my geographic locationGreat culture fitGood value for costReferred to meHow many teammates from Data Science UA were assigned to this project?2-5 EmployeesDescribe the scope of work in detail. Please include a summary of key deliverables.The project involved developing a new chatbot based on artificial intelligence to optimize the operations of medical organizations. For this project, we collaborated with Data Science UA, which included the entire process of hiring a team of AI engineers over the course of a six-month period. **RESULTS & FEEDBACK** What were the measurable outcomes from the project that demonstrate progress or success?The recruitment initiative produced amazing results. Data Science UA effectively identified and onboarded AI developers who blended effortlessly into our team. Their technical expertise and collaborative attitude improved the overall quality of our chatbot development project. Our feedback about new engineers was overall positive. They appreciated Data Science UA's honesty throughout the recruiting process and their swift management of logistical matters, which made their onboarding experience easy.Describe their project management. Did they deliver items on time? How did they respond to your needs?Data Science UA's project management style was impeccable. They provided regular status updates and timely responses. Their clear communication and adherence to timelines ensured a smooth collaboration.What was your primary form of communication with Data Science UA?Virtual MeetingEmail or Messaging AppWhat did you find most impressive or unique about this company?Data Science UA's deep understanding of our project's technical requirements and their ability to identify the right talent was truly impressive. They took the time to understand our company culture, ensuring that the recruited engineers possessed the technical skills and aligned with our values.Are there any areas for improvement or something Data Science UA could have done differently?Regarding the recruitment process, I can confidently say that Data Science UA exceeded our expectations. However, providing even more comprehensive feedback on candidate profiles could further enhance the partnership. --- #### Staff Augmentation for Financial Company **The Project** - Services: Recruiting - Project size: Less than $10,000 - Project length: Aug. 2022 - Feb. 2023 **Project Summary**: Data Science UA provided backend software engineering support for a financial company. Their tasks included processing and storing high-volume financial datasets and Creating ETL pipelines. **Review Rating**: 5.0 - Quality: 4.5 - Schedule: 5.0 - Cost: 4.5 - Willing to Refer: 5.0 **The Reviewer** CEO, Machine Factor Technologies - Industry: Financial services - Client size: 11-50 Employees - Review Type: Online Review - Verified **The Review** — Mar 10, 2023 **Feedback Summary**: Data Science UA provided top-notch development support that satisfied the client's needs. They were proactive in finding a developer with the right skillset for the project and aligned with the client's company culture. They impressed with their exceptional communication skills and enthusiasm. ""We were impressed with their exceptional communication and enthusiasm."" **BACKGROUND** Please describe your company and position. I am the CEO of Machine Factor Technologies Describe what your company does in a single sentence. Machine Factor Technologies is digital assets algorithmic trading hedge fund **OPPORTUNITY / CHALLENGE** What specific goals or objectives did you hire Data Science UA to accomplish? Find Backend Software Engineer **SOLUTION** How did you find Data Science UA? Referral Why did you select Data Science UA over others? High ratings, Great culture fit, Referred to me, Company values aligned What was the size of Data Science UA’s team? 2-5 Employees Describe the scope of work in detail. Please include a summary of key deliverables. Our team was actively searching for Senior Python Data Engineer. Responsibilities: Processing and storing high-volume financial datasets. Creating ETL pipelines using AWS/internal tools. Preprocessing data for our research and development team. Be part of the team responsible for real-time trading implementation. Implement trading models hyper-parameters optimisation pipelines. Hard Requirements: 3+ years experience with Python. Good understanding of analytics, data pipelines and data transformation principles. Proficiency with Pandas and Numpy. **RESULTS & FEEDBACK** What were the measurable outcomes from the project that demonstrate progress or success? Hiring a professional in our budget Describe their project management. Did they deliver items on time? How did they respond to your needs? Data Science UA is extremely responsible and proactive in terms of both client and candidate communication. We knew since day one that finding a developer with the skill set needed would take a long time and effort. However, the Data Science UA team continued searching for candidates even though our requirements were high. Finally, we have found a perfect (both professional and cultural) fit for us with Data Science UA. What was your primary form of communication with Data Science UA? Virtual Meeting, Email or Messaging App What did you find most impressive or unique about this company? We were impressed with their exceptional communication and enthusiasm. Are there any areas for improvement or something Data Science UA could have done differently? No --- #### AI System Dev Support for Industrial Tech Company **The Project** - Services: Custom Software Development - Project size: $200,000 to $999,999 - Project length: Jan. 2020 - Ongoing **Project Summary**: Data Science UA provides development support in building an AI system for an industrial tech company. They are analyzing and validating the AI algorithm to meet the end customer's expectations. **Review Rating**: 4.5 - Quality: 4.5 - Schedule: 5.0 - Cost: 4.5 - Willing to Refer: 5.0 **The Reviewer** VP of Engineering, Everguard.ai - Industry: Other industries - Client size: 11-50 Employees - Review Type: Online Review - Verified **The Review** — Aug 30, 2022 **Feedback Summary**: Data Science UA continues to support the client's project, providing customized AI algorithms for more than 10 end customers. They are using various tools for both project management and communication, including Jira, Slack, and more. So far, the client is happy with the ongoing collaboration. ""Data Science UA manages the team in Ukraine, so we don't need to worry about any people or office management."" **BACKGROUND** Please describe your company and your position there. I'm a VP of engineering and we are developing an industrial safety system using an AI algorithm by a camera and other sensors. We need to develop an accurate sensor measurement and AI algorithm to detect and prevent safety concerns for the customers and reduce accidents and save lives. **OPPORTUNITY / CHALLENGE** For what projects/services did your company hire Data Science UA, and what were your goals? For making a highly accurate AI system, many experienced engineers who had concrete industry level project experiences. In US, it is super hard to find the good engineers and we need to pay at least 3 times more pay than the one in Ukraine. **SOLUTION** How did you select this vendor and what were the deciding factors? I've been working with the Data Science UA last several years and they are one of the best vendor who had a solid pool of good AI engineers. Describe the scope of work in detail, including the project steps, key deliverables, and technologies used. Our team in Ukraine is developing the latest AI algorithm from end to end such as the data collection, labeling, training, algorithm design and testing. Our problem is not easy to solve and the latest AI algorithm cannot be adapted natively. Thus team is analyzing the problem and validate several candidate algorithms and choose the best one then optimize/customize it by the customers' expectation. How many people from the vendor's team worked with you, and what were their positions? Data Science UA gave us one of the best team members for creating it possible. They recruit the best people for our team and keep managing the team as best as possible. I had 8 team members for AI algorithm/data processing team and 3 members of a software development team. **RESULTS & FEEDBACK** Can you share any measurable outcomes of the project or general feedback about the deliverables? We currently had more than 10 customers to provide customized AI algorithm for their unique safety issues. Each of them requires customized AI solution to address the problem. Ukraine team delivers every single delivery on time. We are working together as one team so every delivery is good enough to the required customers. Describe their project management style, including communication tools and timeliness. I am using general managing tools for working with a remote team such as Jira board, Confluence, Github, Slack/Teams etc. We are having team meetings 3 times a week. Once the target goal is set, I give the objectives and goals to the team and manage the development schedule and delivery goals. What did you find most impressive or unique about this company? They find the best possible engineers in Ukraine. Most of them are already motivated and passionate to work on challenging problems. Data Science UA manages the team in Ukraine, so we don't need to worry about any people or office management. Are there any areas for improvement or something they could have done differently? Due to the current chaos between Russia and Ukraine, I cannot travel to Ukraine and meet my team members in person. But hopefully, this issue will be resolved and I can travel to Ukraine and meet the team again --- #### Recruitment Services for AI Startup **The Project** - Services: HR Consulting - Project size: $10,000 to $49,999 - Project length: Jan. 2021 - Ongoing **Project Summary**: An AI startup hired Data Science UA for recruitment services. They’re responsible for finding new AI/ML engineers within the provided criteria. This is for the development of product solutions. **Review Rating**: 5.0 - Quality: 5.0 - Schedule: 5.0 - Cost: 5.0 - Willing to Refer: 5.0 **The Reviewer** Head of Recruitment, Reface - Industry: Other industries - Client size: 51-200 Employees - Review Type: Online Review - Verified **The Review** — Jul 9, 2021 **Feedback Summary**: The team has managed to provide candidates who will join the company. The client is happy with the entire process as they’ve found qualified engineers. Data Science UA is flexible to tasks and quickly provides feedback. Moreover, they professionally manage the entire project and communication.  ""Their recruiting standards are definitely worth mentioning." " **BACKGROUND** Please describe your company and your position there. I'm Head of Recruitment at a rapidly growing AI/ML startup shifting from THE face-swapping app to a platform. The social platform for personalized content creation and unlimited self-expression of the future. **OPPORTUNITY / CHALLENGE** For what projects/services did your company hire Data Science UA? As of the rapid growth of the product last year we required new talented AI/ML engineers to develop our solution. **SOLUTION** How did you select this firm and what were the deciding factors? Data Science UA is the most popular hiring and DS consulting company in Ukraine to widen the AI team in short terms and with an efficient approach. They organize DS conferences and educational events on a regular basis - and they know almost every AI/ML engineer and Data Scientist in person. Describe the project in detail and walk through their service package. We shared requirements for the engineers we are looking for, they have helped us to clarify the requirements and make them more specific. As a next step they shared with us a few profiles of the candidates, which helped to adjust our expectations. Their team runs technical interviews for AI/ML engineers before our team runs the final interviews, it makes us feel confident about the interviewing process from the very beginning. We are quite happy with the people who joined our team. How many resources from the vendor's team worked with you, and what were their positions? Head of recruitment, 3 recruiters **RESULTS & FEEDBACK** Can you share any outcomes from the engagement that demonstrate progress or success? We are happy with the team members their team has found for us. How effective was the workflow between your team and theirs? Quick feedback and flexibility to meet our point of view. They show a high level of professionalism in their processes and communications. What did you find most impressive or unique about this company? Their recruiting standards are definitely worth mentioning. Are there any areas for improvement or something they could have done differently? Everything was great --- #### Recruitment Services for Computer Software Company **The Project** - Services: HR Consulting - Project size: $10,000 to $49,999 - Project length: Oct. 2020 - Jan. 2021 **Project Summary**: A computer software company teamed up with Data Science UA for recruitment services. They were required to hire engineers and data scientists. **Review Rating**: 5.0 - Quality: 5.0 - Schedule: 5.0 - Cost: 4.5 - Willing to Refer: 5.0 **The Reviewer** CTO, YayPay by Quadient - Industry: Other industries - Client size: 51-200 Employees - Review Type: Online Review - Verified **The Review** — Apr 28, 2021 **Feedback Summary**: As a result of Data Science UA's efforts, the new hires have been successfully onboarded. The team's flexibility and professional recruitment processes filled the client's department gap. ""I can confidently say that they showed a very mature level of professionalism in their processes and communications." " **BACKGROUND** Please describe your company and your position there. I'm a Chief Technology Officer at YayPay (by Quadient). YayPay is a SaaS solution for accounts receivable automation. **OPPORTUNITY / CHALLENGE** For what projects/services did your company hire Data Science UA? For recruiting technology resources (engineers and data scientists) What were your goals for this engagement? Hire people **SOLUTION** How did you select Data Science UA? I knew from the market that they can deliver, so I decided to give it a go. Describe the engagement in detail. We have provided initial requirements for the people we are looking for, they have helped us to add clarify those requirements and make them more specific. After that, they have sent a few profiles of the candidates, which helped them to calibrate my expectations for this position. They also run technical interviews for Data Scientists before our team runs the final interviews, so by the moment a candidate ended up in our hands, we already know they are vetted and technically savvy. At some point, we had made our decisions, and we are quite happy with the people who joined our team. What was the team composition? An account manager, main recruiter, and technical expert on their side. **RESULTS & FEEDBACK** Can you share any outcomes from the engagement that demonstrate progress or success? I'm very happy with the team members they were able to find for us. How effective was the workflow between your team and theirs? I could see very quick reactions and a good level of flexibility to meet me in the middle in the cases when it was needed. After working with recruitment agencies across the globe, I can confidently say that they showed a very mature level of professionalism in their processes and communications. What did you find most impressive about this vendor? Their ability to deliver on what they promised Are there any areas for improvement? Not that I can think of --- #### Recruitment Services for Computer Software Company **The Project** - Services: HR Consulting - Project size: Less than $10,000 - Project length: July 2020 - Jan. 2021 **Project Summary**: A computer software company partnered with Data Science UA for recruitment purposes. The client wanted to hire new members for their data science department. **Review Rating**: 4.5 - Quality: 5.0 - Schedule: 5.0 - Cost: 4.5 - Willing to Refer: 5.0 **The Reviewer** Head of HR, 3DLOOK - Industry: Other industries - Client size: 51-200 Employees - Review Type: Online Review - Verified **The Review** — Apr 20, 2021 **Feedback Summary**: Thanks to this collaboration, the client added five new hires to their data science team. Their qualifications met all expectations and the client was pleased with Data Science UA's thorough and speedy search process.    ""Everything was great." " **BACKGROUND** Please describe your company and your position there. I'm Head of HR at a rapidly growing startup that is providing a new level of a customized approach to the apparel and uniform manufacturers and online shoppers, using patented AI technology combined with 3D, CV, ML. **OPPORTUNITY / CHALLENGE** For what projects/services did your company hire Data Science UA, and what were your goals? As of rapid growth of product last year we required new talented team members within DS department to develop our solutions within the set deadline and customer requirements. **SOLUTION** How did you select Data Science UA and what were the deciding factors? The most known and popular hiring agency in Ukraine to widen the DS team in short terms without quality loss. Describe the scope of work in detail, including the project steps, key deliverables, and technologies used. We provided the company with the main requirements for the potential candidates, discussed additional details, then the company started the search, so we had weekly calls to discuss and check the main lists of proposed candidates. How many people from the vendor's team worked with you, and what were their positions? mainly we were communicating with the Sales representatives, recruiters and specifically with founders of the company. **RESULTS & FEEDBACK** Can you share any measurable outcomes of the project or general feedback about the deliverables? During our collaboration, we've widened our DS team with 5 new employees with the company's active assistance. Describe their project management style, including communication tools and timelines. Thorough approach, attentiveness to details and requirements, high speed of search, and quality of the candidates. Weekly status calls to check the results. What did you find most impressive or unique about this company? High quality, authority, responsibility. Are there any areas for improvement or something they could have done differently? Everything was great --- #### Data Consulting for E-Commerce Company **The Project** - Services: Custom Software Development - Project size: $10,000 to $49,999 - Project length: Sep. - Nov. 2020 **Project Summary**: An e-commerce company engaged with Data Science UA for their services concerning data forecasts and analytics. The team was tasked to build predictions from pipeline tendencies and leads. **Review Rating**: 5.0 - Quality: 5.0 - Schedule: 5.0 - Cost: 5.0 - Willing to Refer: 5.0 **The Reviewer** Head of IT Engineering, Tchibo - Industry: Other industries - Client size: 51-200 Employees - Review Type: Online Review - Verified **The Review** — Jan 22, 2021 **Feedback Summary**: The project turned out satisfactory, meeting the client's expectations. Data Science UA managed to work on a prototype and generate leads based on all forecasts they processed. The client commended the team members for their enthusiasm and field expertise. ""They were really engaged, enthusiastic, and emphatic with us." " **BACKGROUND** Please describe your company and your position there. I am Head of IT Engineering in the eCommerce Company. **OPPORTUNITY / CHALLENGE** For what projects/services did your company hire Data Science UA, and what were your goals? It was required to extend and improve the solution in our platform for sales forecasting with predictive analytics. We had large volumes of historical data and we had to make it useful for our sales processes. Our goal was to improve key metrics. Sales forecasting algorithms look for patterns in this data. The detected patterns are further used to score the general tendencies of the deals in the pipeline to build predictions with a high level of accuracy.  **SOLUTION** How did you select Data Science UA and what were the deciding factors? We were referred to Data Science UA by a friend and included them with another firm on a trial project to confirm their competence. Describe the scope of work in detail, including the project steps, key deliverables, and technologies used. We drafted a high-level requirements document outlining the results we needed, and Data Science UA responded with feedback to help us to flesh out our ideas. They were quick to get us a working prototype and final product. How many people from the vendor's team worked with you, and what were their positions? Vendor's team: 3 dedicated developers + project manager. **RESULTS & FEEDBACK** Can you share any measurable outcomes of the project or general feedback about the deliverables? We are satisfied with the project outcomes as we’ve got what we expected on time. Describe their project management style, including communication tools and timelines. We had a weekly meeting with project manager for project status. The development processes went smoothly with no issues What did you find most impressive or unique about this company? Communication. It was always a pleasure to speak with the team, they were really engaged, enthusiastic and emphatic with us. Are there any areas for improvement or something they could have done differently? We are fully satisfied with our collaboration with Data Science UA and will surely contact them for our next project. --- #### IoT Dev for Oil & Gas Company **The Project** - Services: IoT Development - Project size: $50,000 to $199,999 - Project length: June - Nov. 2020 **Project Summary**: Data Science UA provided IoT development services to an oil and gas company. The project entailed data drilling and real-time recording as well as management of information relating to equipment and resources. **Review Rating**: 5.0 - Quality: 5.0 - Schedule: 5.0 - Cost: 5.0 - Willing to Refer: 5.0 **The Reviewer** IT Department Head, Oil & Gas Company - Industry: Energy & natural resources - Client size: 51-200 Employees - Review Type: Online Review - Verified **The Review** — Jan 19, 2021 **Feedback Summary**: Performing tasks as intended, Data Science UA was able to deliver data that could be managed through an online dashboard. They have contributed positively to the oil and gas company through an excellent output. The team defined and adhered to the plans and timeframe. ""I am pretty happy with provided service." " **BACKGROUND** Please describe your company and your position there. We’re an oil and gas company. I’m a Head of IT department. **OPPORTUNITY / CHALLENGE** For what projects/services did your company hire Data Science UA, and what were your goals? Optimization of data obtained from the environment. We aim to maximize production and profits using innovative software and data collection and analysis. **SOLUTION** How did you select Data Science UA and what were the deciding factors? My Mother from Ukraine. I read a lot about Ukraine, visited it. And decided to choose a company from Ukraine. Describe the scope of work in detail, including the project steps, key deliverables, and technologies used. Data Science UA helped to allow drilling data to be recorded real-time. It also includes a wide range of data about environmental conditions such as temperature, oil reserve levels, and equipment performance or status. Managing this data and using it as a strategic asset significantly impacts the financial performance of the company. How many people from the vendor's team worked with you, and what were their positions? From the Data Science UA side, we worked with PM. **RESULTS & FEEDBACK** Can you share any measurable outcomes of the project or general feedback about the deliverables? Data Science UA helped us analyze historical and real-time images & data collected from databases, satellites, drones, IoT sensors allowing. And is now helping us present that information with an interactive online dashboard. Data Science UA helped us make our dream come true. What did you find most impressive or unique about this company? Performed tasks according to plan Are there any areas for improvement or something they could have done differently? I am pretty happy with provided service. --- #### Azure Training & AI Support for Microsoft **The Project** - Services: AI Development, Branding, Direct Marketing, Product Marketing - Project size: Less than $10,000 - Project length: June 2018 **Project Summary**: A productivity tool company partnered with Data Science UA to help with their AI projects. The goal was to reach the target audience, promote the product, and provide Azure training for the AI community. **Review Rating**: 5.0 - Quality: 5.0 - Schedule: 5.0 - Cost: 5.0 - Willing to Refer: 5.0 **The Reviewer** Program Manager, Microsoft Ukraine - Industry: Other industries - Client size: 51-200 Employees - Review Type: Online Review **The Review** — Apr 10, 2023 **Feedback Summary**: With the help of Data Science UA, the client reached and trained AI professionals. They met deadlines and were always available to ensure that the client's needs were met. They had a personalized approach and were communicative and adaptive to changes. ""They were a super responsive team."" **BACKGROUND** Please describe your company and position. I am the Program Manager of Microsoft Ukraine Describe what your company does in a single sentence. Productivity tools for users **OPPORTUNITY / CHALLENGE** What specific goals or objectives did you hire Data Science UA to accomplish? Reach the AI community with Azure cloud possibilities message Hands on Azure training for AI community **SOLUTION** How did you find Data Science UA? Other Why did you select Data Science UA over others? Good value for cost Referred to me Company values aligned What was the size of Data Science UA’s team? 6-10 Employees Describe the scope of work in detail. Please include a summary of key deliverables. Oleksandra and Data Science team became a trusted partner for us in the series of AI community events helping us to reach the relevant audience, promote the product and provide hands-on training for the community. Each step of cooperation was high-level, partner-oriented, and prepared in details. This was an example of win-win partnership where each party reached its goals. DS team managed to build a strong quality community of AI and BigData professionals and feels and understands this domain as no one else in the market. **RESULTS & FEEDBACK** What were the measurable outcomes from the project that demonstrate progress or success? #of AI professionals reached and trained Describe their project management. Did they deliver items on time? How did they respond to your needs? They were a super responsive team. Meets all the deadlines; sleepless for the sake of the client. What was your primary form of communication with Data Science UA? In-Person Meeting What did you find most impressive or unique about this company? Personalized approach, keeping the commitments, super positive and ecological communication style, flexibility. Are there any areas for improvement or something Data Science UA could have done differently? Have not seen so far --- #### Recruitment Services for IT Company **The Project** - Services: Recruiting - Project size: $10,000 to $49,999 - Project length: Jan. 2019 - Dec. 2022 **Project Summary**: Data Science UA provided recruitment services for an IT company. The team was tasked with hiring highly qualified candidates with significant experience in machine learning and AI directions. **Review Rating**: 5.0 - Quality: 5.0 - Schedule: 5.0 - Cost: 5.0 - Willing to Refer: 5.0 **The Reviewer** Country GM, SQUAD - Industry: Other industries - Client size: 1,001-5,000 Employees - Review Type: Online Review - Verified **The Review** — Mar 16, 2023 **Feedback Summary**: With the help of Data Science UA, the client hired 10 AI specialists. Throughout the engagement, they communicated effectively through in-person meetings. Overall, the client was highly satisfied with the results of their partnership. ""DataScience UA helped us to attract highly qualified talents."" **BACKGROUND** Please describe your company and position. I am the Country GM of Squad Describe what your company does in a single sentence. SQUAD is a research and delivery team working on impactful products. We are gathering top notch minds in domains such as Research, Embedded, Hardware, Mobile, QA, Infrastructure, Delivery, Product and Design, and Analytics to collaborate on the latest smart home security/loT. **OPPORTUNITY / CHALLENGE** What specific goals or objectives did you hire Data Science UA to accomplish? Hiring of top-notch research talents **SOLUTION** How did you find Data Science UA? Referral Why did you select Data Science UA over others? Close to my geographic location Great culture fit Good value for cost Referred to me Company values aligned What was the size of Data Science UA’s team? 6-10 Employees Describe the scope of work in detail. Please include a summary of key deliverables. DataScience UA helped us to attract highly qualified talents in Machine Learning and AI directions. **RESULTS & FEEDBACK** What were the measurable outcomes from the project that demonstrate progress or success? Around 10 hired AI Specialists Describe their project management. Did they deliver items on time? How did they respond to your needs? Ideal communication What was your primary form of communication with Data Science UA? In-Person Meeting What did you find most impressive or unique about this company? Best pool of AI talents in Ukraine Are there any areas for improvement or something Data Science UA could have done differently? No. --- #### Recruitment Services for E-Commerce Aggregator **The Project** - Services: Recruiting - Project size: Confidential - Project length: Jan. - Feb. 2023 **Project Summary**: Data Science UA provided recruitment services for an e-commerce aggregator. The team recruited a creative director and an HR generalist for the client. **Review Rating**: 5.0 - Quality: 5.0 - Schedule: 5.0 - Cost: 5.0 - Willing to Refer: 5.0 **The Reviewer** CEO, ECOMX - Industry: Other industries - Client size: 11-50 Employees - Review Type: Online Review - Verified **The Review** — Mar 13, 2023 **Feedback Summary**: The client was thrilled with the team's impeccable management of the project. Data Science UA was quick to respond to the client's needs. Their streamlined approach simplified the process, enabling the client to focus on other tasks. Overall, the experience was nothing short of exceptional. ""Everything was executed flawlessly, and I couldn't think of any areas that require improvement."" **BACKGROUND** Please describe your company and position. I am the CEO of ECOMX Describe what your company does in a single sentence. ECOMX is an e-Commerce aggregator. **OPPORTUNITY / CHALLENGE** What specific goals or objectives did you hire Data Science UA to accomplish? Recruit Creative Director Recruit HR Generalist **SOLUTION** How did you find Data Science UA? Referral Why did you select Data Science UA over others? High ratings, Great culture fit, Good value for cost, Referred to me, Company values aligned What was the size of Data Science UA’s team? 2-5 Employees Describe the scope of work in detail. Please include a summary of key deliverables. Data Science UA recruited for us a Creative Director and a HR Generalist for our company. **RESULTS & FEEDBACK** What were the measurable outcomes from the project that demonstrate progress or success? People hired Describe their project management. Did they deliver items on time? How did they respond to your needs? I was thrilled with the impeccable management of my project! Every deliverable was promptly delivered on time, and the team's speedy responses were beyond impressive. Overall, the experience was nothing short of exceptional. What was your primary form of communication with Data Science UA? Virtual Meeting, Email or Messaging App What did you find most impressive or unique about this company? I was delighted by the lightning-fast pace at which everything was executed - I never had to endure any prolonged waiting periods. This streamlined approach significantly simplified my life and allowed me to focus on other tasks with ease. Are there any areas for improvement or something Data Science UA could have done differently? I'm extremely satisfied with the hiring process and the new additions to our team. Everything was executed flawlessly, and I couldn't think of any areas that require improvement. --- #### End-to-End Service for Adjunct Professor **The Project** - Services: BI & Big Data Consulting & SI - Project size: $10,000 to $49,999 - Project length: Jan. 2017 - Ongoing **Project Summary**: Data Science UA is tasked with developing an end-to-end platform for an adjunct professor's educational projects and consulting. The client works with a team of managers and technical experts. **Review Rating**: 5.0 - Quality: 5.0 - Schedule: 5.0 - Cost: 5.0 - Willing to Refer: 5.0 **The Reviewer** Adjunct Professor - Industry: Education - Client size: 501-1,000 Employees - Review Type: Online Review - Verified **The Review** — Oct 13, 2021 **Feedback Summary**: More than 2,000 people use the client's courses thanks to Data Science UA. The vendor had a great team that provided end-to-end services and solutions for their needs. Overall, everything has been going well for both parties. ""They provide a great end-to-end services and solutions for my needs in Data Science and AI."" **BACKGROUND** Please describe your company and your position there. I am an adjunct professor in a number of universities. **OPPORTUNITY / CHALLENGE** For what projects/services did your company hire Data Science UA? Educational projects and consulting. **SOLUTION** How did you select this vendor and what were the deciding factors? We evaluated a number of companies in Ukraine and Data Science UA clearly was standing out as a partner of choice. Describe the project in detail and walk through the stages of the project. End-to-end management of educational courses. How many resources from the vendor's team worked with you, and what were their positions? Team of managers and technical experts. **RESULTS & FEEDBACK** Can you share any outcomes from the project that demonstrate progress or success? More than 2000 attendees for the courses that we organized. How effective was the workflow between your team and theirs? They had a great team of managers and technical experts. What did you find most impressive or unique about this company? They provide a great end-to-end services and solutions for my needs in Data Science and AI. Are there any areas for improvement or something they could have done differently? Everything was great. --- #### Data Consulting for IT Services Company **The Project** - Services: Cloud Consulting & SI - Project size: $10,000 to $49,999 - Project length: Sep. - Nov. 2020 **Project Summary**: An IT services company teamed up with Data Science UA for data consulting for a health-tech platform. They aimed to deliver a plan and SoW for a refactoring and architectural rebuild of a medical database. **Review Rating**: 5.0 - Quality: 5.0 - Schedule: 5.0 - Cost: 5.0 - Willing to Refer: 5.0 **The Reviewer** CEO, Global Talent - Industry: Other industries - Client size: 11-50 Employees - Review Type: Online Review - Verified **The Review** — Apr 20, 2021 **Feedback Summary**: Though the project is protected by an NDA contract, Data Science UA completed and delivered it on time and within the client's budget. The client has no other words but positive feedback for their exceptional technical skills, strong soft skills, and creative solutions shown by the team. ""They have exceptional technical skills matched with equally strong soft skills and creative solutions." " **BACKGROUND** Please describe your company and your position there. CEO and Co Founder **OPPORTUNITY / CHALLENGE** For what projects/services did your company hire Data Science UA? Data Architect and Pathfinder Management for health-tech platform What were your goals for this project? To deliver a plan and SoW for a first phase refactoring and architectural rebuild of a medical database. **SOLUTION** How did you select Data Science UA? DS UA was selected for their prior domain expertise in medical and pharmaceutical technology. Describe the project in detail. Detail of the project is protected under NDA What was the team composition? CTO DS Manager Data Engineer  Delivery Manager **RESULTS & FEEDBACK** Can you share any outcomes from the project that demonstrate progress or success? Definition and SoW was delivered on time and within budget. Minor issues with presentation and delivery of the report meant that the second phase of work was not awarded although the overall feedback and performance was positive. How effective was the workflow between your team and theirs? Exceptional What did you find most impressive about this company? They have exceptional technical skills matched with equally strong soft skills and creative solutions. Are there any areas for improvement? Minor observations on presentation and delivery of final results but overall no significant areas for improvement. --- ## Portfolio & Awards ### AI agent for real-time automated trading insights Tasks Build a machine learning model to forecast price movements across selected trading instruments. Develop an AI agent that interprets model outputs to inform automated decision-making processes. Integrate reporting functionality to generate and deliver performance metrics and KPIs. Implement an external trigger system (e.g., email and webhook) to automatically activate the agent and handle follow-up responses. Challenges Financial markets are unpredictable; historical patterns may not hold during major geopolitical events or policy changes, especially within the UK market. Extracting predictive signals from structured market data and unstructured sources like news or social media required significant effort, with no guarantee of impact.  Solutions Developed adaptive models with online learning capabilities to regularly retrain on new data and adjust to changing market trends. Integrated macroeconomic indicators and real-time event data into the model to improve responsiveness to market shifts. Used automated feature engineering (AutoFE) tools to rapidly test and refine a wide range of input variables. Worked closely with financial experts to vet model features and interpret market behavior accurately. Deployed advanced NLP pipelines to extract signals from news headlines, social sentiment, and regulatory updates. Hosted models on high-performance infrastructure, optimizing serving latency and throughput using FastAPI. Outcomes Delivered an AI agent capable of handling real-time price predictions for multiple instruments. Enabled automatic activation via email or webhook, with the agent retrieving inputs, executing analysis, and sending back KPI reports. Reduced manual intervention in forecasting and reporting workflows. Created a scalable foundation for automated decision-support tools in financial operations. ### Product identification model for retail audit The opportunity The client required a high-performance Object Detection model to replace their existing pipeline, which was limited by licensing and accuracy issues. The primary goal was to develop a custom SOTA model capable of identifying products in complex retail environments with high precision, specifically for on-shelf drink identification and planogram monitoring. Our approach We developed a state-of-the-art model from scratch, training it on diverse, high-complexity datasets to ensure 20% better performance than existing market alternatives. Our work focused on the Data Pipeline, Core Detection Model, and Model Optimization. We delivered the final codebase and repository under an MIT license, optimized for further integration into mobile or web environments. Value created Our YOLO26s model outperformed ResNet-50 benchmarks for densely packed items. We achieved a 20% boost in accuracy: mAP@50-95 0.59 (vs 0.49), Recall 0.83 (vs 0.55), and Precision 0.90 (vs 0.83). This enables automated “share-of-shelf” analysis and instant planogram tracking with minimal human error. By delivering a scalable detection engine, we’ve built the foundation for the upcoming SKU Classification phase. Technologies Used SOTA Object Detection Architectures PyTorch for training & experimentation MLflow TFLite Albumentations Model quantization ### AI assistant for enhanced learning experience Tasks Improve access to learning materials for platform users. Convert unstructured content (PDFs and video presentations) into a searchable, structured format. Enable fast and intuitive information retrieval through natural language queries. Lay the groundwork for scalable AI-based learning tools. Challenges Much of learning content presented was locked in static formats like PDFs and recorded videos. The lack of content structure made it difficult to implement intelligent search or any personalized assistance. Solutions Used OCR to digitize and structure course content from PDFs and video transcripts based on predefined business logic. Implemented a vector database to index content semantically. Deployed a Retrieval-Augmented Generation (RAG) system using the o3-mini large language model to enable contextual responses to user queries. Built a simple, secure interface with Streamlit for learner access. Hosted all infrastructure in AWS Cloud for scalability and performance. Designed the solution as an MVP, with ongoing iterations based on user feedback. Outcomes Reduced time learners spend searching for relevant materials by over 70%. Made course materials accessible via conversational queries, improving user interaction and satisfaction. Established a solid infrastructure foundation for future AI features. Continued platform development is supported by real-world usage insights and feedback from learners. ### AI platform for client-consultant interactions Tasks Establish a single client-consultant touchpoint for client questionnaires. Enable advanced analytics for consultants. Generate HRPP, Salary reports, and Graded Pay Structure. Challenges The main challenge was to create a system that ensures continuous availability, enhances customer experience, boosts consultant effectiveness, and minimizes their data-related tasks. Solutions Developed a secure, single-touchpoint service with dynamic dashboards and drill-down capabilities. Built an autonomous system with a modern, user-friendly interface. Used historical data for predictive analytics and personalized recommendations. Outcomes Improved customer satisfaction with a user-friendly service, enhanced consultants’ effectiveness, enabling greater project scalability, reduced consultants’ data tasks, freeing resources, and showcased EY’s commitment to modern solutions and brand value. Technologies Used Python (pandas, numpy, scipy, scikit-learn) PyTorch LSTM ### AI client engagement & personalization agent Tasks Develop machine learning models to analyze client behavior, segment users, and predict preferences. Build a personalized recommendation engine for workout plans, services, and offers. Fine-tune the LLM to reflect the company’s brand tone, gym-specific procedures, and customer support guidelines. Build an ETL pipeline to unify data from client’s mobile app, gym systems, and CRM/ERP into a centralized repository. Implement secure cloud storage for models, logs, and backups using AWS S3. Challenges Client preferences shifted over time, requiring continuous model updates, while new clients or services lacked sufficient data for meaningful recommendations. The platform needed to comply with data privacy regulations such as GDPR while maintaining user trust.  Solutions Client data used for modeling was anonymized using salted one-way hashes; personally identifiable information was excluded from analytics workflows. Custom instructions, prompts, and reinforcement feedback were used to shape the assistant’s responses, ensuring brand consistency and accuracy in gym-related queries. Built a robust data pipeline to extract, clean, and centralize information from multiple systems, improving data reliability for ML models.  Combined behavior prediction, segmentation, and recommendations into one agent that could adapt based on real-time user feedback and platform usage patterns. The mobile app was updated with a clear privacy policy and tools for users to view, export, or delete their personal data. Outcomes Successfully deployed a secure and compliant AI assistant that recommends content, manages schedules, and engages clients in personalized conversations. Improved user satisfaction through more relevant recommendations and faster response times. Maintained data privacy and built trust with clients through transparent handling of sensitive information. Laid a scalable foundation for ongoing machine learning improvements and LLM updates. ### Renewable energy supply prediction model Tasks Develop a predictive model on the wind energy production forecast Analyze historical data for accuracy Implement and test the model Challenges Accurately forecast wind energy production based on historical data. Solutions Developed a predictive model for wind energy production Utilized historical data for training and testing the model Implemented machine learning techniques to enhance forecast accuracy Outcomes Model Forecast – mean Absolute Percentage Error was less than 10 ### Review classification system for a taxi aggregator   Client: A big taxi management company with reviews in Ukrainian, English, etc. Challenge: Our main challenge was to build a reliable classification system that would allow the internal analyst team to quickly and efficiently analyze text reviews in multiple languages. Additional challenges were: text quality (grammar, spelling issues distort prediction quality), multilingual pipeline (no out-of-the-bag model can equally well work with different languages), quality control (business-specific metrics had to be defined to assess the performance), and custom-tailored categories (not just general ones, but also those defined by industry). Solution: First, we built a preprocessing pipeline with language detection, spelling correction, machine translation, etc. Then, on top of it, a custom model based on TCN layers was trained to detect business-specific categories in the reviews. Translation quality, precision, and recall metrics for each specific category were checked with the predefined business goal. Results: A fast, reliable tool that allowed the client’s quality assurance team to quickly, easily analyze driver’s performance, provide overall user satisfaction metrics, promptly solve critical issues. Technology stack Python, NLTK, Transformers, Tensorflow, etc.   ### Core ML Engineers team for viral AI app Tasks Build the first core engineering team of AI/ML specialists. Identify top-tier candidates with expertise in cutting-edge AI research and development. Establish long-term collaboration on hiring for R&D teams to support innovation.   Challenges Defining highly specific criteria for candidates aligned with Reface’s unique product development goals. Attracting top talent in a competitive AI landscape. Solutions Conducted a detailed analysis of Reface’s technical needs and long-term R&D objectives. Implemented a targeted recruitment strategy leveraging industry networks and AI-specific talent pools. Created a streamlined hiring process to evaluate both technical skills and cultural fit. Outcomes Successfully hired Reface’s first core team of AI/ML engineers. Established a long-term partnership for ongoing AI talent acquisition. Supported Reface in maintaining its position as a globally recognized leader in AI-driven personalized content creation. ### ML-powered transaction classification Tasks Develop a classification model to help customers understand their spending habits. Create an adjustable ML model to profile credit and debit transactions. Build a clustering ensemble to define regular and irregular transactions. Challenges The main challenge was to create a competitive advantage by utilizing AI to distinguish the financial app from others and to grow expertise in advanced analytics and machine learning. Solutions An adjustable ML model that profiles customer transactions by merchant, purchase type, and income. A clustering ensemble that categorizes each user’s transactions as regular or irregular. Outcomes The ML saving advisor became one of the most used features of the app. The first version of the model allowed accurate labeling of regular and irregular transactions in 80% of cases. Technologies Used Python (scikit-learn, gradient boosting) Data warehouse (AWS Redshift, Google BigQuery) Power BI   ### AI-powered outreach platform Tasks Enable real-time audio and text recognition Provide instant insights for sellers Develop a new feature for customizing video and audio content Challenges Enabling real-time audio and text recognition, providing instant insights for sellers. Developing a new feature for customizing video and audio content, aiming to enhance the platform’s functionality. Solutions Released real-time audio and text recognition & processing to offer immediate information to sellers Developed a new feature of video and audio customization Data annotation for multilanguage audio data Outcomes Immediate information delivery through real-time recognition Enhanced platform functionality with customizable video and audio content Multilanguage data annotation for broader reach ### NLP algorithm based on word embeddings Client:Ukrainian startup that provides market research services in the retail industry. The company collects data from all the popular retail stores in Ukraine and sells insights extracted. In particular, the company provides price-setting assistance based on competitor analysis Challenge: The company has encountered a problem while adding new products to its database. A simple comparison did not work since identical products may have different names in different stores, and not all stores provide complete information about the product's characteristics. Therefore, a more profound approach was required.  Solution:Our team has developed an algorithm based on word embeddings (vector representations of words). Using BERT-based library sentence-transformers, we incorporated the power of natural language processing for this task. First, by calculating the embedding of the product name and then comparing it with the embeddings of products in the database, we managed to find items with a certain similarity threshold. Results:The developed algorithm can now quickly find similar products in a vast database, and it is possible to set a threshold for the desired similarity. The system also extracts all the possible characteristics from the product name (such as size, brand, and country of origin). Technology stackPython (nltk, sentence-transformers, scipy, pymongo), MongoDB, Docker. ### Automated price optimization system   Client A national store network with hundreds of locations in Ukraine. The field is highly competitive with several other similar networks.   Challenge Production sale prices are changing with time. Sometimes they are lagging behind the demand and competitors. The network wanted the exactly optimal prices to maximize the revenue, which was challenging to do manually.   Solution The customer turned to Data Science UA to develop such a system. The design took into account multiple surrounding factors. It distributed the goods in categories and adjusted prices for each of them. The result fitted the price-demand distribution to improve the revenue for each product.   Technology stack Python   ### AI-powered review classification model   Client: Eastern review aggregator company that assembles text reviews from multiple resources (Google reviews, Yelp, etc.). Challenge: Build and deploy a model to categorize English text reviews according to the business-predefined categories. The main challenge was to build a relational category scheme with multiple levels (first being the most abstract and all consequent ones more discrete) and then train a custom model to predict categories in the text according to the scheme adequately. Additionally, a small model to highlight category-specific text in the review had to be implemented. Solution: First, we built a preprocessing pipeline with grammar correction, tokenization (with menu items treated as a special case), etc. After that, training data describing the complex category scheme was collected and properly labeled. On it, a custom BERT-based model was trained. Using text-distance measures simple text highlighting model was built, in order to immediately highlight predicted categories in the text. Results: After deployment, the client successfully integrated the model into their service as a dashboard, so that restaurant chains could easily filter, compare and analyze the performance of individual restaurants. The highlighting model was also used to provide accessible feedback from the review text directly Technology stack: Python, NLTK, SpaCy, Transformers, Tensorflow, scheduling, MySQL.   ### Automated data collection system in Pharma Tasks Audit current IT architecture. Analyze reporting processes across departments. Recommend solutions for analytic function optimization. Gather requirements for reporting and analytics. Define master data systems for each category. Propose new IT architecture for system integration. Outline development plan for the new system. Challenges The main challenge was to develop a comprehensive strategy to automate data collection and reporting processes, integrate various data systems, and improve data-driven decision-making capabilities for Servier Ukraine. Solutions Established unified reporting standards for all data categories. Created a single Master Data system per category. Enabled automated data exchange across systems to reduce manual tasks. Built an automated reporting system for recurring reports. Recommended MS Power BI as the primary reporting tool. Outcomes Automated data collection and reporting. Enhanced data integration and minimized silos. Strengthened decision-making with predictive analytics. Reduced manual tasks, boosting data efficiency. Improved user experience with a modern interface. ### ML clustering & predicting the outflow of clients Client: Company: comp&ben prepaid corporate services from France (worked with an Italian office)    Challenge: The work was centered on machine learning (ML) - clustering and predicting the outflow of customers, but along the way, we also completed a data management task (DM) - defined data dictionaries and data requirements (SMB data only).   Solution: 1. We created a complete description of the data in the main source (CRM) - a data dictionary.2. Determined the requirements for those fields that must be filled by sales team in CRM for the model to work.3. Experimentally determined outflow based on customer return data after checking competitors' offers.4. Created a model for clustering customers based on their behavioral characteristics.5. Created a customer churn model and a flow of transition from one cluster to another to prevent churn. Forecasting horizon - 2 months, since 1 month is enough for the company to return customers and 2-3 weeks to prepare new campaigns to retain and return customers.6. Created a dashboard in MS PowerBI to work with clustering data and track customer churn and retention.     Results: As a result of our work, the sales department of the Italian office was divided into two types of employees: hunters were engaged in attracting new customers, and farmers - in retaining current customers. According to preliminary data (the project was completed in the spring of 2020 when there was a challenging situation with the coronavirus in Italy), the client began to measure and track the outflow. As a result, the outflow decreased by 20% compared to the first measurements in 2 months of work. ### Data collection and analysis tool Data Science UA is building a client-facing product for a Big Four company in the HR domain. The client’s goal is to develop a client-facing data collection and analysis web tool that will provide HR professionals with the latest market analytics, industry trends, and recommendations on the future development of HR function in their companies. Current stage: web tool development (stage 1 out of 3) The infrastructure used: MS Azure Stack Main goals: - Ensure continuous availability of data collection system and data analysis results; - Improve customer experience and the level of satisfaction by providing easy-to-use service; - Increase customer satisfaction and brand value by implementing modern service delivery solutions; - Reduce employees involvement in data collection, processing, and analysis and thus minimize losses and free up resources; - Improve employees effectiveness and increase their involvement with more projects and clients, and therefore make scaling possible;- Use historical data for predictive and prescriptive analytics building personalized recommendations ### Document description tool (BERT-based model) Client: A B2B consulting company willing to automatically keep track of new trends from reports. Challenge: Having a report text, summarize it in a few sentences, and provide key categories present in the text. The main challenge here is to extract the data, feed the summarization model, and find categories from a predefined list of those categories present in a whole dataset. Solution: Upon running the BERT-based summarization model, we had to manually scroll through a sample dataset to define possible categories; then, the categorization model was trained. Results: A short, complete document description tool accessible within seconds that allows for quick comparison and filtering of the documents in question.  Technology stack Python, NLTK, SpaCy, Transformers, MongoDB. ### NLP Case - text classification Client: A big B2C company with a massive amount of text reviews willing to better understand what their customers like and dislike about their services. Solution: Use a set of NLP techniques to preprocess (fix grammar, spelling, machine translation, etc.) and categorize (using BERT, TCN, and other neural nets), allowing the business analysis team to quickly and efficiently browse through hundreds of thousands of reviews.   Results: A set of metrics that describe actual business performance, 10x efficiency gain, and the elimination of hundreds of human work-hours spent reading through the texts.  ### Customer-centric data model Client: Ukrainian insurance company of one of the largest European Insurance Group Challenge: The company had the following challenges: - low quality of customer data (duplicates and incomplete data) - lack of documentation on data stored in the company's IT systems - lack of a master system for client data - lack of data entry and verification standards - inability to make a decision based on data (the same indicators when calculating them in different systems give different results)  Solution: Our team has done the following: - full inspection of all processes that generate, process, store and use customer data (interviews with representatives of different departments);- a study of training materials for employees who generate data;- a study of the main reports that use customer data;- a study of the customer's mobile application for the collection, use and display of customer data;- a study of the available documentation on IT architecture and systems of the customer.   Results: - we provided recommendations for the development and interoperability of systems (in terms of data collection, storage, exchange and use), work with data from partners, data analysis, data management at the company level, as well as recommendations for working with data at each stage of customer data for one line of insurance products; - defined critical customer data, master system for them, rules and standards of their collection and validation;- identified options for action in case of data conflicts;- defined a work plan for three months with specific actions that will help move to a customer-centric data model and completely eliminate duplicates, as well as improve the quality of customer data;- examples of the creation of necessary documentation are provided: data flow diagram, data models, data dictionaries, EDM, API of documentation, schedule of exchanges and matrix of roles (for each system separately). ### Sales prediction Client The company sells health and beauty products to multiple distribution points.   Challenge Sale predictions were crucial for the production and distribution plans. However, the customer completed them manually based on average values. The company wanted to produce relatable predictions for each product with the possibility to adjust them.   Solution The solution to a problem was a formula that allowed the company to calculate the predictions independently for each next period. Current trends also played a part in the calculation. The prediction process was no longer manual and followed clearly defined steps, leading to automatic sale predictions. The solution provided a visual representation of the process, including dynamic dashboards.   Technology stack   Python, Microsoft PowerBI ### Compliant AI agent for sterility monitoring Tasks Develop advanced computer vision models to detect protocol violations in aseptic environments.  Build an AI agent to analyze visual input in real time, interpret events, and issue alerts based on risk levels. Implement a centralized dashboard for event logging, reporting, and trend analysis. Enable multi-channel notifications with escalation logic for unacknowledged alerts. Ensure the system meets pharmaceutical industry compliance and integrates with the company’s existing infrastructure.Challenges Maintaining false positive and false negative rates under 8.5% and 9.8%, respectively, was essential to avoid alert fatigue or missed violations. Accurate labeling of complex actions across large video datasets was time-consuming but critical to model performance. Continuous monitoring across multiple camera feeds generated significant data volumes that needed to be stored, retrieved, and audited efficiently. Solutions The team annotated over 7,000 cleanroom images and used targeted data augmentation and synthetic generation to simulate real-world conditions: glare, shadows, occlusions. Image processing pipelines were tuned to normalize lighting fluctuations before model inference, improving detection stability. The AI agent used a configurable rules engine to evaluate combinations of detections and escalate based on predefined risk scenarios (e.g., lack of goggles near sterile zones).  Developed an automated logging mechanism that records all safety-related events, enabling detailed audit trails for regulatory reporting.Outcomes  Deployed a real-time sterility monitoring system across the client’s manufacturing zones. Enabled fast, accurate detection and escalation of non-compliant procedures, reducing human oversight burden. Maintained target false alert rates, balancing safety and efficiency. Provided traceable audit logs and incident reports to support internal QA and external regulatory inspections. Built a scalable foundation for continuous model improvem ### Industry Recognitions - Top 100 in 2021 IT Employer of the Year in Ukraine - Top 3 in Ukraine(# of open Data Science vacancies) ## Key Clients - Ernst & Young - Outreach.io - Reface - EVA - Uklon - Helen Marlen - Odin - Adthena - Everguard - NFlux - Servier - ShelfSet LLC ## Packages ## Locations (2) ### London, England (Headquarters) - 10 York Road - London SE1 7ND - England - 76 - 100 employees - Phone: +380990552392 ### Zürich, Switzerland - CreativeSpace Luegislandstrasse 105, Zürich, Switzerland - Zürich 8051 - Switzerland - 2 - 5 employees ## Contact Data Science UA [Send a message](https://clutch.co/profile/data-science-ua)