# Fast Data Science Fast Data Science Reviews (4), Pricing, Services & Verified Ratings - 4.9 out of 5 average review rating - 3 connections joined Fast Data Science's Network [Visit Website](https://fastdatascience.com) [Get a Custom Proposal](https://clutch.co/profile/fast-data-science) **Data Science Consulting** Consulting services specializing in text, images, unstructured data, and healthcare/pharmaceuticals. Certified by Microsoft as an Azure Data Scientist. ## Company Information - Minimum project size: $1,000+ - Hourly rate: $200 - $300 - Number of employees: 2 - 9 - 1 Locations: - London, England (Headquarters) - Founded in 2018 ## Services, Focus Areas, Industries, and Clients ### Service Lines - 90% AI Development - 10% BI & Big Data Consulting & SI ### Focus Areas - BI & Big Data Focus: - 100% Other BI & analytics - BI & Big Data Solutions: - 80% Microsoft BI & data solutions - 20% Other BI & data solutions - AI Expertise: - 70% Natural Language Processing - 30% Machine Learning ### Industries - 50% Medical - 50% Information technology ### Clients - 50% Midmarket ($10M - $1B) - 50% Enterprise (>$1B) ## Pricing Snapshot Average rating for cost based on this provider's reviews: 5.0 out of 5 **What Clients Have Said** *(This summary is based on verified Clutch reviews.)*: Fast Data Science is praised for its good value and budget-friendly pricing. Clients highlight effective communication and timely deliverables, with no specific project costs disclosed. Overall, they provide high-quality services that fit well within client budgets. **Most Common Project Size**: $10,000 to $49,000 based on 1 review *(Pricing information for this provider is based on reviews where the project size was available.)* ### Pricing by Service - AI Development: Confidential based on 3 reviews - BI & Big Data Consulting & SI: $10,000 to $49,000 based on 1 review - Video Production: Confidential based on 1 review - Web Development: Confidential 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) ### Fast Data Science Review Insights Overall Review Rating: 4.9 - Quality: 5.0 - Schedule: 5.0 - Cost: 5.0 - Willing to Refer: 5.0 ### Top Mentions - Timely (4 mentions) - Communicative (2 mentions) - Experienced (1 mentions) - High-quality work (1 mentions) - Team players (1 mentions) ### Review Highlights **Cultural Fit and Value for Money** Fast Data Science is noted for its great cultural fit and good value for cost, making it an attractive choice for clients looking for budget-friendly yet effective solutions. **High Client Satisfaction and No Improvement Areas** Clients report high satisfaction with Fast Data Science's services, with no significant areas for improvement mentioned, indicating a strong alignment with client expectations. **Capability in Handling Complex Data Projects** The company successfully handles complex data projects, transforming large datasets into actionable insights and interactive tools, showcasing its technical expertise and problem-solving skills. **Timely Delivery and Responsiveness** Clients consistently praise Fast Data Science for delivering projects on time and being highly responsive to their needs, ensuring smooth project execution and client satisfaction. **Strong Communication Skills** The company is commended for its effective communication, using virtual meetings and emails to keep clients updated and involved, ensuring clarity and understanding throughout projects. **Proficiency in NLP and AI Solutions** Fast Data Science is highly skilled in implementing natural language processing and AI solutions, catering to diverse needs like clinical data extraction, sensitive information identification, and survey analysis. ### Fast Data Science Reviews #### Data Analysis & Interactive Dashboard for Nonprofit Survey (Featured Review) **The Project** - Services: BI & Big Data Consulting & SI - Project size: $10,000 to $49,999 - Project length: June 2020 - Ongoing **Project Summary**: Fast Data Science has leveraged natural language processing (NLP) and machine learning technology to analyze nearly 1.2 million open-ended responses to a women's rights survey. They've visualized the data, too. **Review Rating**: 5.0 - Quality: 5.0 - Schedule: 5.0 - Cost: 5.0 - Willing to Refer: 5.0 **The Reviewer** Sr Communications Officer, Women's Rights Nonprofit - Industry: Other industries - Client size: 1-10 Employees - Review Type: Online Review - Verified **The Review** — Dec 10, 2020 **Feedback Summary**: Based on the data, Fast Data Science has created infographics and presented their findings in accessible language. They're now working on an interactive dashboard that will allow site visitors to deep dive into the content. They've opened the internal staff's eyes to future campaigns. ""We were extremely pleased with every aspect of this project and with our working relationship." " **BACKGROUND** Please describe your company and your position there. Through its vast network of National Alliances, our nonprofit is activating the global movement for reproductive, maternal and newborn health and rights. I work as the Senior Communications Officer, working closely on the "What Women Want: Demands for Quality Healthcare from Women & Girls" campaign that heard from more than 1 million women and girls in 114 countries about the one thing they want most for their own reproductive and maternal healthcare through an open-ended survey. **OPPORTUNITY / CHALLENGE** For what projects/services did your company hire Fast Data Science? The "What Women Want: Demands for Quality Healthcare from Women & Girls" campaign resulted in the collection of nearly 1.2 million open-ended survey responses from women and girls around the world, in 18 languages. Fast Data Science helped us analyze the requests to help us create advocacy agendas around those requests; these advocacy agendas are currently being used to elevate the voices and demands of women to create policy change. Fast Data Science used NLP and machine learning to analyze the survey responses, and to create an interactive dashboard for advocates interested in examining the data. What were your goals for this project? We wanted to understand the data we had in our hands, and be able to examine it and use it in a way that would allow our group to elevate the demands of nearly 1.2 million women around the world. **SOLUTION** How did you select Fast Data Science? Fast Data Science had all the qualities we were looking for in our large data project - in-depth understanding of the technology needed to achieve our goals, as well as excellent staff capable of explaining the complex technical aspects of the work in a way that our entire team could understand. And, as the name implies, Fast Data Science was extremely fast, helping us meet our deadlines. Describe the project in detail. After connecting with Fast Data Science, we held an initial kickoff conversation where the complexities of our project were laid out. We then shared all of the data and work that we had done on the project with Fast Data Science to run their analysis and begin the work. Within one month, which included several conversations and refining of our requests as our side understood the power of the technology available to us, we had an our data not only analyzed but shared back with our team in plain language and in clear infographics. We then began a new phase of the project where Fast Data Science converted our massive amount of static data into an interactive dashboard using Python and other tools. What was the team composition? I worked most closely with the Data Science Team, with others from my organization's side joining in on phone calls and planning sessions. **RESULTS & FEEDBACK** Can you share any outcomes from the project that demonstrate progress or success? Fast Data Science helped us analyze nearly 1.2 million open-ended survey responses, allowing us to clearly see what our data was saying, and is now helping us present that information for an external audience with an interactive online dashboard that will allow users to perform their own deep dives into our data. This dashboard was a dream project that we were not sure was actually possible to create - Fast Data Science helped us realize this dream and we are very pleased with the work. How effective was the workflow between your team and theirs? Fast Data Science was extremely responsive, and available for calls, sharing of information, and even presentations with our global team on a regular basis. We communicated over email and through Zoom, and our communications were always efficient, informative, and enjoyable. What did you find most impressive about this company? I had no idea the power of data science technology! What Fast Data Science was able to do for my organization, in such a short amount of time, was unbelievable and opened our eyes to what is possible in the future for our other campaigns. We were also really happy to have found a company that was able to communicate with our team of non-data scientists in a way that was clear and totally understandable. Are there any areas for improvement? We were extremely pleased with every aspect of this project and with our working relationship with the Fast Data Science team. --- #### AI Tool Development for Nonprofit Organization **The Project** - Services: AI Development, Video Production, Web Development - Project size: Confidential - Project length: July 2021 - June 2025 **Project Summary**: Fast Data Science developed an AI tool for a nonprofit organization. The tool used AI and natural language processing to identify and quantify the risk of clinical trial uninformativeness. **Review Rating**: 4.5 - Quality: 5.0 - Schedule: 5.0 - Cost: 5.0 - Willing to Refer: 5.0 **The Reviewer** Deputy Director, Nonprofit Organization - Industry: Non-profit - Client size: 1,001-5,000 Employees - Review Type: Online Review - Verified **The Review** — Apr 13, 2026 **Feedback Summary**: The tool had excellent accuracy in predicting clinical trial protocol risk of noninformativeness. Fast Data Science met all deadlines on time and on budget. The team was responsive to requests and delivered high-quality work. They were also described as cheerful and capable. ""They met all deadlines on time and on budget."" **BACKGROUND** Please describe your company and position. I am the Deputy Director of a non-profit company Describe what your company does in a single sentence.Non-profit foundation funding Global Health research and Global Development. **OPPORTUNITY / CHALLENGE** What specific goals or objectives did you hire Fast Data Science to accomplish?Engage in AI tool product support and ongoing enhancement of the AI tool (from V1.0 TB and HIV coverage to subsequent versions supporting trial protocol reviews for research in other diseases).Develop a browser-based tool which uses AI and natural language processing to identify and quantify the risk of clinical trial uninformativeness.Quantitatively measure the accuracy of the AI tool by comparing the tool's classification of trial protocols (trials whose results are already known).Create software requirements specifications (SRS), design document, and end-user documentation for the AI uninformativeness risk classification tool.Author scholarly manuscript describing the AI tool and achieve publication of the manuscript in a refereed journal.Create instructional videos for training of clinical trial reviwer end-users in the use of the AI tool. **SOLUTION** How did you find Fast Data Science?ReferralWhy did you select Fast Data Science over others?High ratingsGreat culture fitGood value for costReferred to meHow many teammates from Fast Data Science were assigned to this project?1 EmployeeDescribe the scope of work in detail. Please include a summary of key deliverables.Develop a browser-based tool which uses AI and natural language processing to identify and quantify the risk of clinical trial uninformativeness. The tool reads and parses the text of trial protocols and identifies key features of the trial design, which are fed into a risk model. The application runs in a browser and features a graphical user interface that allows a user to drag and drop the PDF of the trial protocol and visualize the risk indicators and their locations in the text. The user can correct inaccuracies in the tool’s parsing of the text. The tool outputs a PDF report listing the key features extracted. V1.0 of the tool is focused HIV and tuberculosis trials and was subsequently extended to more pathologies in future. Results: On a manually tagged dataset of 300 protocols, the tool was able to identify the condition of a trial with 100% area under curve (AUC), presence or absence of statistical analysis plan with 87% AUC, presence or absence of effect estimate with 95% AUC, number of subjects with 69% accuracy, and simulation with 98% AUC. **RESULTS & FEEDBACK** What were the measurable outcomes from the project that demonstrate progress or success?Excellent accuracy in predicting clinical trial protocol risk of noninformativeness. On a manually tagged dataset of 300 protocols, the tool was able to identify the condition of a trial with 100% area under curve (AUC), presence or absence of statistical analysis plan with 87% AUC, presence or absence of effect estimate with 95% AUC, number of subjects with 69% accuracy, and simulation with 98% AUC. Manuscript was published.Describe their project management. Did they deliver items on time? How did they respond to your needs?They met all deadlines on time and on budget. All deliverables were of high quality. Responses to the original scope-of-work brief and subsequent enhancement requrests were top-notch. Bravo! Would engage Fast Data Science and Thomas Wood again!What was your primary form of communication with Fast Data Science?Virtual MeetingWhat did you find most impressive or unique about this company?Careful design, capable engineering, excellent software QA, comprehensive documentation and training, cheerful responses to difficult problems.Are there any areas for improvement or something Fast Data Science could have done differently?No areas for improvement arose during the engagement. Superb Fast Data Science performance on this AI development engagement. --- #### Data Analysis & Interactive Dashboard for Nonprofit Survey **The Project** - Services: BI & Big Data Consulting & SI - Project size: $10,000 to $49,999 - Project length: June 2020 - Ongoing **Project Summary**: Fast Data Science has leveraged natural language processing (NLP) and machine learning technology to analyze nearly 1.2 million open-ended responses to a women's rights survey. They've visualized the data, too. **Review Rating**: 5.0 - Quality: 5.0 - Schedule: 5.0 - Cost: 5.0 - Willing to Refer: 5.0 **The Reviewer** Sr Communications Officer, Women's Rights Nonprofit - Industry: Other industries - Client size: 1-10 Employees - Review Type: Online Review - Verified **The Review** — Dec 10, 2020 **Feedback Summary**: Based on the data, Fast Data Science has created infographics and presented their findings in accessible language. They're now working on an interactive dashboard that will allow site visitors to deep dive into the content. They've opened the internal staff's eyes to future campaigns. ""We were extremely pleased with every aspect of this project and with our working relationship." " **BACKGROUND** Please describe your company and your position there. Through its vast network of National Alliances, our nonprofit is activating the global movement for reproductive, maternal and newborn health and rights. I work as the Senior Communications Officer, working closely on the "What Women Want: Demands for Quality Healthcare from Women & Girls" campaign that heard from more than 1 million women and girls in 114 countries about the one thing they want most for their own reproductive and maternal healthcare through an open-ended survey. **OPPORTUNITY / CHALLENGE** For what projects/services did your company hire Fast Data Science? The "What Women Want: Demands for Quality Healthcare from Women & Girls" campaign resulted in the collection of nearly 1.2 million open-ended survey responses from women and girls around the world, in 18 languages. Fast Data Science helped us analyze the requests to help us create advocacy agendas around those requests; these advocacy agendas are currently being used to elevate the voices and demands of women to create policy change. Fast Data Science used NLP and machine learning to analyze the survey responses, and to create an interactive dashboard for advocates interested in examining the data. What were your goals for this project? We wanted to understand the data we had in our hands, and be able to examine it and use it in a way that would allow our group to elevate the demands of nearly 1.2 million women around the world. **SOLUTION** How did you select Fast Data Science? Fast Data Science had all the qualities we were looking for in our large data project - in-depth understanding of the technology needed to achieve our goals, as well as excellent staff capable of explaining the complex technical aspects of the work in a way that our entire team could understand. And, as the name implies, Fast Data Science was extremely fast, helping us meet our deadlines. Describe the project in detail. After connecting with Fast Data Science, we held an initial kickoff conversation where the complexities of our project were laid out. We then shared all of the data and work that we had done on the project with Fast Data Science to run their analysis and begin the work. Within one month, which included several conversations and refining of our requests as our side understood the power of the technology available to us, we had an our data not only analyzed but shared back with our team in plain language and in clear infographics. We then began a new phase of the project where Fast Data Science converted our massive amount of static data into an interactive dashboard using Python and other tools. What was the team composition? I worked most closely with the Data Science Team, with others from my organization's side joining in on phone calls and planning sessions. **RESULTS & FEEDBACK** Can you share any outcomes from the project that demonstrate progress or success? Fast Data Science helped us analyze nearly 1.2 million open-ended survey responses, allowing us to clearly see what our data was saying, and is now helping us present that information for an external audience with an interactive online dashboard that will allow users to perform their own deep dives into our data. This dashboard was a dream project that we were not sure was actually possible to create - Fast Data Science helped us realize this dream and we are very pleased with the work. How effective was the workflow between your team and theirs? Fast Data Science was extremely responsive, and available for calls, sharing of information, and even presentations with our global team on a regular basis. We communicated over email and through Zoom, and our communications were always efficient, informative, and enjoyable. What did you find most impressive about this company? I had no idea the power of data science technology! What Fast Data Science was able to do for my organization, in such a short amount of time, was unbelievable and opened our eyes to what is possible in the future for our other campaigns. We were also really happy to have found a company that was able to communicate with our team of non-data scientists in a way that was clear and totally understandable. Are there any areas for improvement? We were extremely pleased with every aspect of this project and with our working relationship with the Fast Data Science team. --- #### AI & ML Development for Medical Software Company **The Project** - Services: AI Development - Project size: Confidential - Project length: July 2025 - Mar. 2026 **Project Summary**: Fast Data Science provided AI and machine learning (ML) development services for a medical software company. The team handled an NLP project to parse text data and used LLMs to improve the client's AI engine. **Review Rating**: 5.0 - Quality: 5.0 - Schedule: 5.0 - Cost: 5.0 - Willing to Refer: 5.0 **The Reviewer** VP AI & NLP, Inspirata Inc. - Industry: Information technology - Client size: 11-50 Employees - Review Type: Online Review - Verified **The Review** — Apr 14, 2026 **Feedback Summary**: Fast Data Science delivered a software solution that could parse complex PDFs for clinical data extraction. The team communicated effectively through email, online calls, and weekly meetings. Moreover, Fast Data Science was responsive, attentive to the client's needs, and willing to assist. ""Fast Data Science's focus was on what we needed, and they were consistently willing to assist."" **BACKGROUND** Please describe your company and position.I am the VP AI and NLP of Inspirata Inc.Describe what your company does in a single sentence.Medical software engineering focusing on cancer informatics **OPPORTUNITY / CHALLENGE** What specific goals or objectives did you hire Fast Data Science to accomplish?Assistance with decomposing and parsing complex PDF's for patient data and clinical trial protocols.Use of LLM's to solve component of a problem in our AI Engine technology. **SOLUTION** How did you find Fast Data Science?ReferralWhy did you select Fast Data Science over others?High ratingsPricing fit our budgetGreat culture fitGood value for costHow many teammates from Fast Data Science were assigned to this project?1 EmployeeDescribe the scope of work in detail. Please include a summary of key deliverables.NLP project for Parsing clinical text data. **RESULTS & FEEDBACK** What were the measurable outcomes from the project that demonstrate progress or success?Software to parse complex PDF's for clinical data extraction.Describe their project management. Did they deliver items on time? How did they respond to your needs?Thomas was basically included as part of our AI team - weekly meetings and other updates.  Communcation was very good through emails and online calls. Deliverables were on time.What was your primary form of communication with Fast Data Science?Virtual MeetingEmail or Messaging AppWhat did you find most impressive or unique about this company?Thomas was very responsive and essentially became part of our team for the duration of the project. Fast Data Science's focus was on what we needed, and they were consistently willing to assist.Are there any areas for improvement or something Fast Data Science could have done differently?All good. --- #### AI Dev for Pharmaceutical AI Solutions Company **The Project** - Services: AI Development - Project size: Confidential - Project length: Jan. 2024 - Apr. 2026 **Project Summary**: Fast Data Science provided AI and machine learning development services for a pharmaceutical AI solutions company. The team developed multiple models to identify sensitive information in clinical documents. **Review Rating**: 5.0 - Quality: 5.0 - Schedule: 5.0 - Cost: 5.0 - Willing to Refer: 5.0 **The Reviewer** Director, Product Management, Real Life Sciences - Industry: Other industries - Client size: 51-200 Employees - Review Type: Online Review - Verified **The Review** — Apr 13, 2026 **Feedback Summary**: Thanks to Fast Data Science's work, the client saw a significant decrease in project processing times. The team was highly responsive and went above and beyond the client's expectations. Moreover, they were highly skilled and experienced, enabling them to move quickly. ""They move quickly because they have the right skills and experience."" **BACKGROUND** Please describe your company and position.I am the Director, Product Management of Real Life SciencesDescribe what your company does in a single sentence.Real Life Sciences helps Pharma Sponsors meet regulations EMA Policy 0070 and HC PRCI **OPPORTUNITY / CHALLENGE** What specific goals or objectives did you hire Fast Data Science to accomplish?Identify sensitive information in clinical documents using AI **SOLUTION** How did you find Fast Data Science?Online SearchWhy did you select Fast Data Science over others?High ratingsPricing fit our budgetGreat culture fitGood value for costHow many teammates from Fast Data Science were assigned to this project?1 EmployeeDescribe the scope of work in detail. Please include a summary of key deliverables.Fast data science helped develop multiple models to help better identify sensitive information in clinical documents **RESULTS & FEEDBACK** What were the measurable outcomes from the project that demonstrate progress or success?We saw a significant decrease in project processing times. Describe their project management. Did they deliver items on time? How did they respond to your needs?Thomas from Fast Data Science was always on target amd goes well above and beyondWhat was your primary form of communication with Fast Data Science?Virtual MeetingEmail or Messaging AppWhat did you find most impressive or unique about this company?They move quickly because they have the right skills and experienceAre there any areas for improvement or something Fast Data Science could have done differently?Not at all, they are and have been a pleasure to work with --- ## Portfolio & Awards ### Clinical Trial Risk Tool We developed a tool using Natural Language Processing for a client in the pharmaceutical space to assist experts to estimate the risk of a clinical trial ending uninformatively. You can read more about it on the project website. We were contacted by a client in the pharmaceutical space who wanted a tool to assist reviewers in quantifying the risk of a clinical trial protocol. A protocol is  a PDF document, typically up to 200 pages long, and contains a complete description of the plan of a trial: where it will take place, how many subjects will be recruited (the sample size), which interventions are to be tested, and how the statistical analysis is to be conducted.     ### Harmony We developed a harmonisation tool using Natural Language Processing to allow researchers to conduct meta-analyses of mental health studies in collaboration with the University of Ulster, University College London, and the Universidade Federal de Santa Maria in Brazil, for the Wellcome Trust’s Data Prize in Mental Health. You can read more on the project website. ### Predicting customer spend How can you use data science and machine learning to predict how much your customers will spend? ### Predicting employee turnover Machine learning model to predict turnover of employees in an organisation of 3 million workers ### Finding molecules and proteins in scientific literature I have worked on a number of different projects where a client needed to parse scientific literature and identify occurrences of molecules or proteins. As an example, the molecule on the right is Aspirin. This is still a trademark of Bayer in some countries. But in a paper it could appear under acetylsalicylic acid, 2-acetoxybenzenecarboxylic acid,C9H8O4, or a number of identifiers such as DB00945. There could also be identifiers that refer to other molecules, or identifiers that refer to only one version of a molecule. Another example I have encountered often in clinical papers is the gene ERBB2, which is important in certain types of breast cancer. ERBB2 is also called Erb-B2 Receptor Tyrosine Kinase, HER2, HER-2 and many other names. These names often also refer to the protein expressed by the gene. Many names are similar to common English words, and are not always capitalised in text. Because of these pathological effects, the task of identifying names of proteins, genes and molecules in scientific literature is fraught with difficulty. I have developed several tried and tested techniques to disambiguate these terms. Usually I need a number of annotated examples to start with, and I will train a machine learning model to learn from these examples and annotate new publications as they come in. This can be deployed on the client’s servers and provide daily updates on a dashboard. This allows a client to monitor the literature in real time for publications around a particular molecule, protein or gene, or to spot trends in advance. ### Predicting customer orders A client in the retail industry had a fleet of vehicles delivering produce at different times of day. They used third party logistics software to plan the delivery schedules, however an element of the delivery schedules that was hard to plan was the unloading time of the vehicle when it arrived at the store. Fortunately there was a system in place for recording vehicle ignition events, GPS location, and geofencing to identify the arrival and departure times of delivery vehicles, and past schedules were available to identify the quantity and type of product delivered on each drop, which driver was in charge, and the time of day and type of vehicle used. Using this trove of logged data I was able to train a simple regression model that would predict the unloading time of any future delivery at the time that the schedule is being generated. This allowed the client to save money on driver overtime, disruption caused by late deliveries, and fines due to drivers working longer than their legally permitted hours. ### Conversions improvement using machine learning With one customer in the recruitment industry I found that the web form that was used for jobseeker signup was very long. By analysing the fields in the form I was able to establish that users were confused by some fields, and lingered for a long time in some areas.   Since users also uploaded their CV which contains explicitly lots of personal information, as well as implicit information such as the job type or salary that someone was looking for, I was able to train a deep neural network on past signup data over several years, to analyse the CV and fill out some of the fields in the signup form automatically.    This allowed a field to be removed, which boosted the conversion rate of the form by 7%, measured by A/B testing.   This is one small example of what can be achieved combining text analysis and conversion optimisation techniques.   If you have a long signup form on your website please let me know and I may be able to deploy a machine learning model to improve the user experience and boost your conversions.     ### Clinical Trials Protocols When a pharmaceutical company develops a drug, it needs to pass through several phases of trials before it can be approved by regulators.   Before the trial is run, the drug developer writes a document called a protocol. This contains key information about how long the trial will run for, what is the risk to participants, what kind of treatment is being investigated, etc.   The problem is that each protocol is up to 200 pages long and the structure can vary.   For one pharma company I developed and trained a deep learning tool to predict more than 50 output variables from a clinical trial protocol. This allows pharma companies and regulators to analyse and quantify large numbers of protocols, allowing more accurate cost estimation.   The technique can be extended to other industries where large unstructured or semi-structured documents are the norm.   If you have a problem of this nature please get in contact with me and I will be glad to discuss. ## Key Clients - Boehringer Ingelheim ## Packages ## Locations (1) ### London, England (Headquarters) - 55 Sotheby Road - London N5 2UP - England - 2 - 5 employees - Phone: 07906331524 ## Connections - George Cernile (Inspirata) - Jonathan Nolan (Real Life Sciences) ## Contact Fast Data Science [Send a message](https://clutch.co/profile/fast-data-science) ### Connect on Social - [LinkedIn](https://www.linkedin.com/company/fastdatascience) - [Facebook](https://www.facebook.com/fastdatascienceltd) - [X](https://twitter.com/fastdatascienc1)