12 of 12 Contract Statistical Modelling Jobs in the UK

crime across the NHS. Further information about our work and annual plan for delivering this is available on our website. The Data Scientist role requires expertise in machine learning, statistical analysis, anomaly detection, and strong communication and collaboration skills. Key responsibilities include developing innovative models, designing, applying, and optimising models in a dynamic environment. The role is critical in … project planning, using data to drive business objectives, and defining project directions to achieve financial targets. With a deep understanding of data science, including machine learning, predictive modelling, and deep learning, the Data Scientist will tackle complex challenges and extract actionable insights from diverse datasets. They will lead model development and ensure solutions meet business and government standards. The … NHSCFA goals, ensuring accountability for innovative outcomes. Utilising the latest advanced methods, they will embed analytics into the organisation to enhance fraud detection within the NHS. Clear communication of statistical outputs and results to non-technical stakeholders is crucial, influencing decisions like criminal intervention, policy changes, or risk metrics based on data-driven insights. The role demands adherence to More ❯

crime across the NHS. Further information about our work and annual plan for delivering this is available on our website. The Data Scientist role requires expertise in machine learning, statistical analysis, anomaly detection, and strong communication and collaboration skills. Key responsibilities include developing innovative models, designing, applying, and optimising models in a dynamic environment. The role is critical in … project planning, using data to drive business objectives, and defining project directions to achieve financial targets. With a deep understanding of data science, including machine learning, predictive modelling, and deep learning, the Data Scientist will tackle complex challenges and extract actionable insights from diverse datasets. They will lead model development and ensure solutions meet business and government standards. The … NHSCFA goals, ensuring accountability for innovative outcomes. Utilising the latest advanced methods, they will embed analytics into the organisation to enhance fraud detection within the NHS. Clear communication of statistical outputs and results to non-technical stakeholders is crucial, influencing decisions like criminal intervention, policy changes, or risk metrics based on data-driven insights. The role demands adherence to More ❯

crime across the NHS. Further information about our work and annual plan for delivering this is available on our website. The Data Scientist role requires expertise in machine learning, statistical analysis, anomaly detection, and strong communication and collaboration skills. Key responsibilities include developing innovative models, designing, applying, and optimising models in a dynamic environment. The role is critical in … project planning, using data to drive business objectives, and defining project directions to achieve financial targets. With a deep understanding of data science, including machine learning, predictive modelling, and deep learning, the Data Scientist will tackle complex challenges and extract actionable insights from diverse datasets. They will lead model development and ensure solutions meet business and government standards. The … NHSCFA goals, ensuring accountability for innovative outcomes. Utilising the latest advanced methods, they will embed analytics into the organisation to enhance fraud detection within the NHS. Clear communication of statistical outputs and results to non-technical stakeholders is crucial, influencing decisions like criminal intervention, policy changes, or risk metrics based on data-driven insights. The role demands adherence to More ❯

analysis and insights in support of national and regional projects. The post-holder will bring, and be supported to further develop, real technical analytical expertise across disciplines such as modelling, statistics, data science, operational research and/or health economics. The post-holder will be passionate about the contribution they can make to effective decision making. They will be … and organisational activity and financial plans Hold extensive knowledge of NHS data and able to create linked datasets Select and apply the most appropriate analytical technique, underpinned by robust statistical understanding Provide advanced analytical services to strategic healthcare projects and programmes in the form of descriptive analyses, prospective service modelling, retrospective analyses and evaluation Utilise modelling and … forecasting techniques to predict future need and demand. Lead economic and quantitative evaluations using econometric and decision modelling techniques Automate reporting and develop data pipelines Scope and develop reporting outputs, including dashboard development in Tableau and/or FDP Lead delivery of analytical work programmes, matrix managing across multiple staff not under direct line management Person Specification Education/ More ❯

analysis and insights in support of national and regional projects. The post-holder will bring, and be supported to further develop, real technical analytical expertise across disciplines such as modelling, statistics, data science, operational research and/or health economics. The post-holder will be passionate about the contribution they can make to effective decision making. They will be … and organisational activity and financial plans Hold extensive knowledge of NHS data and able to create linked datasets Select and apply the most appropriate analytical technique, underpinned by robust statistical understanding Provide advanced analytical services to strategic healthcare projects and programmes in the form of descriptive analyses, prospective service modelling, retrospective analyses and evaluation Utilise modelling and … forecasting techniques to predict future need and demand. Lead economic and quantitative evaluations using econometric and decision modelling techniques Automate reporting and develop data pipelines Scope and develop reporting outputs, including dashboard development in Tableau and/or FDP Lead delivery of analytical work programmes, matrix managing across multiple staff not under direct line management Person Specification Education/ More ❯

and product assortments to maximise retention, basket size and lifetime value. Role Overview As a Specialist Retail Customer Analyst, you'll own end-to-end customer analytics: extracting and modelling sales and behavioural data, building dashboards and presenting actionable consumer insights to cross-functional teams. Key Responsibilities Develop customer segmentation, CLV and propensity models to inform targeting and promotions … experience in retail/FMCG Bachelor's or Master's in a quantitative discipline (e.g., Economics, Statistics, Data Science) Expert SQL skills and proficiency in Python or R for statistical modelling Hands-on dashboarding experience with Tableau or Power BI Demonstrable experience designing and analysing A/B tests Strong storytelling and stakeholder-management skills Full UK work More ❯

Be Doing: Work closely with fellow data scientists to explore how AI/ML can unlock insights and improve decision-making. Perform advanced analysis on large, complex datasets using statistical and modelling techniques. Build, test, and tune ML models (especially NLP or computer vision) using Python and modern ML libraries, all within Google Cloud Platform (GCP) . Optimise More ❯

Be Doing: Work closely with fellow data scientists to explore how AI/ML can unlock insights and improve decision-making. Perform advanced analysis on large, complex datasets using statistical and modelling techniques. Build, test, and tune ML models (especially NLP or computer vision) using Python and modern ML libraries, all within Google Cloud Platform (GCP) . Optimise More ❯

models, and deliver data-driven insights to support business decisions. Key Responsibilities: - Analyse and pre-process time series data; build forecasting and predictive models. - Develop machine learning algorithms and statistical models. - Collaborate with business and technical teams to deliver data science solutions. - Optimise data pipelines in partnership with data engineers. - Communicate insights clearly to stakeholders and support data-driven More ❯

Analyst, Data Scientist or similar. Proven experience and strong knowledge of regression analysis Experience building multiple MMM's for at least 2 years, A/B tests and other statistical modelling techniques. Proficiency in Python and/or R. Excellent proficiency in SQL to and working with data warehousing technologies (e.g. Snowflake, Databricks). Ability to use data More ❯

business through performing analytics across the Credit life cycle. Supporting the creation and delivery of monitoring for credit risk and fraud models. Devising model strategies for credit assessment utilising statistical model outputs balancing risk and business targets. Input to IFRS9 accounting standards, including investigating issues and maintaining data. The collection, validation, cleansing and transformation of data. Gathering requirements, identifying More ❯

prepare data for advanced analytics and machine learning applications. Analyse complex datasets to uncover trends, patterns, and actionable insights that drive business or operational outcomes. Build, prototype, and evaluate statistical and machine learning models to solve real-world problems, testing feasibility and estimating impact before full deployment. Engineer and implement ML-based solutions, owning the full life cycle - from … prototyping to production deployment, integration, and ongoing monitoring. You are proficient in Python and its data/ML ecosystem (eg pandas, scikit-learn, PyTorch, TensorFlow), and you can apply statistical and machine learning techniques confidently in real-world settings. You have deployed models into live systems and understand how to make ML operational - whether that means working with APIs More ❯