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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Scientist - **Company:** Cardiff and Vale University Health Board - **Location:** Wimbledon, UK - **Experience:** Expert - **Salary:** £72,719.0 - £83,505.0 - **Contract:** Permanent contract - **Skills:** Clean Code Principles, Artificial Intelligence, Data Analysis, ArcGIS (Software), Unit Testing, Microsoft Azure, Data Cleansing, Information Engineering, Data Governance, Data Infrastructure, Data Integration, Extract Transform Load (ETL), Decision Support Systems, Github, Revision Control Systems, Monitoring of Systems, Python (Programming Language), Machine Learning, PRINCE2, Quantum GIS (QGIS), Power BI, SQL Databases, Computational Statistics, Unstructured Data, Feature Engineering, Snowflake, Apache Spark, Model Validation, DataRobot, Machine Learning Operations, Marketplace, Software Version Control - **Published:** October 8, 2026 - **Apply:** https://www.jobs.nhs.uk/candidate/jobadvert/D9491-26-0011/ats-direct-apply ## About the Role We are looking for an exceptional Senior Data Scientist who combines deep technical expertise and methodological rigour with strategic thinking, collaboration and a strong focus on measurable impact., We are looking for an accomplished Data Scientist with substantial experience in advanced statistics, predictive modelling and Machine Learning, together with strong technical capability in Python and SQL. You will understand how to translate complex problems into clearly defined analytical questions, determine whether Data Science is the appropriate solution, select the right methodology and ensure models are appropriately designed, tested, validated and evaluated. You will combine technical depth with strategic and analytical judgement. You will be comfortable challenging assumptions and methodologies, working through ambiguity and explaining complex technical concepts, including uncertainty and limitations, to senior and non-technical audiences. You will also be highly collaborative, working across Data Science, Data Engineering and Analytics, as well as with clinicians, commissioners, operational teams and other stakeholders, to develop solutions that address real-world healthcare challenges., * Educated to master's level or equivalent level of experience of working at a senior level in specialist area of data science. * Evidence of continued professional development., * Demonstrated experience of coordinating projects in complex and challenging environments. * Significant experience & knowledge of probability and statistical inference, regression, time series modelling, experimental design & A/B testing, Bayesian methods, model validation * Significant knowledge and experience of supervised & unsupervised machine learning, ensemble methods * Knowledge of ETL/ELT processes * Significant experience of successfully operating in a politically sensitive environment. * Knowledge and experience of designing end to end pipelines * Knowledge and experience of technical to business translation * Significant experience of working with Data Engineers * Knowledge and experience of agile and or hybrid solution delivery * Knowledge and experience of storytelling to a very senior audience * Experience of managing risks and reporting * Experience of unit testing * Experience of drafting briefing papers and correspondence for a senior audience. * Experience of monitoring budgets and business planning processes. * Demonstrated experience in a Healthcare environment. * Experience of setting up and implementing internal processes and procedures. * Experience in applying statistical, data science and machine learning techniques to real-world problems in a healthcare setting. * Experience in managing, structuring and analysing NHS datasets (e.g. SUS, CSDS and MHSDS, primary care data, performance data). * Experience in developing and maintaining reproducible analytical pipelines (RAP) and workflows. * Experience working with large, complex, and sensitive datasets, ideally in a healthcare or public sector setting. * Extensive knowledge and experience with data visualisation tools, e.g. PowerBI. * Working knowledge of geospatial visualisation and analysis solutions, e.g. ArcGIS, QGIS, etc. * Experience in developing dashboards and automated reporting solutions. * Experience with using Snowflake to interrogate structured and unstructured data, write complex code, leverage Marketplace solutions, and develop ML models. * Strong understanding of population health management and epidemiological principles, and experience in choosing and deploying the most effective analytical techniques for each scenario. Skill and Ability, * Ability to analyse very complex issues where material is conflicting and drawn from multiple sources. * Numerate and able to understand complex financial issues combined with deep analytical skills. * Knowledge of Financial Systems e.g. monitoring budget management, processing * Comprehensive knowledge of project principles, techniques and tools, such as Prince 2. * Ability to prepare and produce concise communications for dissemination to a broad range of stakeholders as required. * Ability to provide and receive complex, sensitive and contentious information and present complex and sensitive information to large groups and senior stakeholders. * Demonstrated capability to plan over short, medium and long-term timeframes and adjust plans and resource requirements accordingly. * High proficiency in Python and SQL. * Understanding of Snowflake's machine learning capabilities and integration with tools like Python, Spark, or DataRobot. * Strong understanding of data governance, privacy, and security principles including IG and GDPR. * Familiarity with version control tools (e.g. GitHub or Azure DevOps) and collaborative coding practices. * Proficiency in R, * Ability to work as part of a team and work flexibly to provide support to other departments and teams as and when necessary. * Ability to work without supervision, but escalating when appropriate, providing specialist advice to the organisation, working to tight and often changing timescales. * Tenacity: demonstrates high levels of self-belief, drive, enthusiasm and stamina to achieve goals and see things through. * Ability to work effectively under pressure and to manage competing priorities. * Self-confident and motivated. * Ability to work effectively in multi-disciplinary teams, successfully engaging and communicating with technical and non technical clinical and operational senior stakeholders in a logic and compelling manner. * Strong problem-solving and critical thinking skills. * Willingness to learn and adapt to new tools, technologies, and methodologies. ## Description You will work across Data Science, Data Engineering and Analytics, applying advanced statistical, Machine Learning and AI approaches to complex healthcare and organisational problems and ensuring that successful solutions are reproducible, scalable and capable of delivering measurable value. This reflects the JD's requirement for technical leadership, methodological authority, advanced modelling and translation of strategic and operational challenges into Data Science problems., Success will not be measured by the number or complexity of models developed. We are interested in whether Data Science solutions can move successfully through the full lifecycle: Problem definition methodology data preparation modelling validation deployment monitoring evaluation measurable benefit You will provide senior technical and methodological authority, challenging analytical approaches where necessary and ensuring that methods and models are appropriate for the problem being addressed. You will work closely with Data Engineers to ensure that the data preparation, orchestration, transformation and pipelines underpinning Data Science products are robust, reproducible and scalable. You will help embed Reproducible Analytical Pipelines (RAP), MLOps, automation, version control, testing and model monitoring, enabling successful models to become sustainable analytical products rather than remaining experimental prototypes. You will also provide methodological assurance around model validity, uncertainty, assumptions, limitations, bias, fairness, explainability and model drift, helping ensure that Data Science and AI solutions are appropriately validated, monitored and understood. These responsibilities are explicitly reflected in the JD's requirements for model risk, validation, audit, bias, fairness, drift and explainability. Ultimately, we are looking for someone who can connect technical and methodological excellence with measurable organisational and healthcare benefit. Why join us? You will work within an integrated Intelligence & Insights function supporting South East and South West London, alongside Data Scientists, Data Engineers, Population Health specialists and wider analytical teams working with rich and complex health and care data. Your work will support Population Health Management, strategic commissioning, inequalities, planning and service improvement, providing the opportunity to apply advanced methods to questions with direct relevance to healthcare services and the populations they serve. You will join an environment where Data Science, Data Engineering and Analytics work together, creating the opportunity to take successful ideas beyond experimentation and turn them into sustainable analytical capability that supports better evidence and decision-making. If you are an accomplished Data Scientist who combines technical depth, methodological authority, strategic thinking and collaboration with a determination to turn Data Science into measurable real-world value, we would like to hear from you. 1. Lead advanced Data Science, statistical modelling, Machine Learning and AI provide technical and methodological leadership in the design and development of predictive, inferential, causal, forecasting, optimisation, risk-stratification and population-segmentation solutions 2. Translate strategic and operational problems into high-value Data Science solutions work with stakeholders to define problems, identify appropriate analytical approaches and prioritise use cases capable of delivering meaningful and measurable organisational or healthcare benefit. 3. Ensure analytical and methodological rigour throughout model development set standards for model design, experimentation, testing, validation and evaluation, ensuring models are statistically robust, reproducible and appropriate for their intended purpose. 4. Operationalise Data Science from development through to production work closely with Data Engineers and analysts to establish end-to-end processes covering data preparation, feature engineering, modelling, validation, deployment, monitoring and ongoing evaluation. The JD specifically expects the postholder to oversee the development of data-engineering pipelines and data preparation supporting models. 5. Develop scalable Reproducible Analytical Pipelines (RAP) and drive automation move manual and difficult-to-reproduce analytical processes towards automated, transparent, auditable and reusable workflows, improving the efficiency and scalability of Data Science and the wider analytical function. 6. Drive measurable improvements in analytical productivity and delivery use Data Science, AI and automation to reduce processing time and manual effort, increase reuse, improve analytical performance and release capacity for higher-value analytical work. 7. Provide assurance and responsible governance of models and AI lead model validation and audit, ensure risks, assumptions and limitations are documented, and establish appropriate monitoring of bias, fairness, explainability and model drift. 8. Work collaboratively across Data Science, Data Engineering and Analytics develop solutions jointly with Data Platform Engineers, analysts, clinicians and operational stakeholders, ensuring models are supported by robust data preparation and can operate effectively in real-world settings. 9. Translate complex Data Science into actionable insight and decision support interpret model outputs, uncertainty and implications and communicate them clearly to senior, clinical, operational and non-technical audiences, enabling advanced analytics to support better decision-making. 10. Develop Data Science capability across the wider analytical function mentor analysts and technical colleagues, provide expert guidance on appropriate analytical methods, coach colleagues in modelling and storytelling, develop a Data Science community of practice and evaluate emerging techniques and technologies. We are looking for someone who can:identify the right problem select the appropriate methodology build a technically rigorous solution automate and productionise it demonstrate quantifiable benefit. That is the clearest expression of what distinguishes the role: not simply the ability to undertake sophisticated Data Science, but the ability to turn it into a rigorous, operational and measurable capability.