1 to 25 of 104 Statistical Modelling Jobs in England

seeking a Senior Data Scientist with a strong background in Biostatistics to help leading life sciences and pharmaceutical organisations modernise and scale their statistical modelling capabilities. This role combines statistical expertise with modern data engineering practices, enabling the development of robust, reproducible, and production-ready analytical solutions. … work closely with biostatisticians, data scientists, and technical stakeholders to improve modelling approaches and deploy scalable solutions within cloud-based environments. Key Responsibilities Partner with biostatisticians and cross-functional teams to enhance statistical modelling methodologies Design and develop scalable R-based modelling workflows and packages Implement ...

seeking a Senior Data Scientist with a strong background in Biostatistics to help leading life sciences and pharmaceutical organisations modernise and scale their statistical modelling capabilities. This role combines statistical expertise with modern data engineering practices, enabling the development of robust, reproducible, and production-ready analytical solutions. … work closely with biostatisticians, data scientists, and technical stakeholders to improve modelling approaches and deploy scalable solutions within cloud-based environments. Key Responsibilities Partner with biostatisticians and cross-functional teams to enhance statistical modelling methodologies Design and develop scalable R-based modelling workflows and packages Implement ...

seeking a Senior Data Scientist with a strong background in Biostatistics to help leading life sciences and pharmaceutical organisations modernise and scale their statistical modelling capabilities. This role combines statistical expertise with modern data engineering practices, enabling the development of robust, reproducible, and production-ready analytical solutions. … work closely with biostatisticians, data scientists, and technical stakeholders to improve modelling approaches and deploy scalable solutions within cloud-based environments. Key Responsibilities Partner with biostatisticians and cross-functional teams to enhance statistical modelling methodologies Design and develop scalable R-based modelling workflows and packages Implement ...

seeking a Senior Data Scientist with a strong background in Biostatistics to help leading life sciences and pharmaceutical organisations modernise and scale their statistical modelling capabilities. This role combines statistical expertise with modern data engineering practices, enabling the development of robust, reproducible, and production-ready analytical solutions. … work closely with biostatisticians, data scientists, and technical stakeholders to improve modelling approaches and deploy scalable solutions within cloud-based environments. Key Responsibilities Partner with biostatisticians and cross-functional teams to enhance statistical modelling methodologies Design and develop scalable R-based modelling workflows and packages Implement ...

seeking a Senior Data Scientist with a strong background in Biostatistics to help leading life sciences and pharmaceutical organisations modernise and scale their statistical modelling capabilities. This role combines statistical expertise with modern data engineering practices, enabling the development of robust, reproducible, and production-ready analytical solutions. … work closely with biostatisticians, data scientists, and technical stakeholders to improve modelling approaches and deploy scalable solutions within cloud-based environments. Key Responsibilities Partner with biostatisticians and cross-functional teams to enhance statistical modelling methodologies Design and develop scalable R-based modelling workflows and packages Implement ...

enhance supply chain performance. This is an exciting opportunity for an analytically minded professional with a strong foundation in statistics and experience applying advanced modelling techniques to real-world business problems. Working closely with cross-functional stakeholders, you will leverage statistical modelling, machine learning, and predictive analytics … improve forecasting accuracy, optimise inventory, and drive operational efficiency. Key Responsibilities: Apply statistical modelling and machine learning techniques to address supply chain challenges, including demand forecasting, inventory optimisation, and replenishment planning. Develop, test, validate, and deploy predictive models using robust statistical methodologies, including regression analysis, time series ...

enhance supply chain performance. This is an exciting opportunity for an analytically minded professional with a strong foundation in statistics and experience applying advanced modelling techniques to real-world business problems. Working closely with cross-functional stakeholders, you will leverage statistical modelling, machine learning, and predictive analytics … improve forecasting accuracy, optimise inventory, and drive operational efficiency. Key Responsibilities: Apply statistical modelling and machine learning techniques to address supply chain challenges, including demand forecasting, inventory optimisation, and replenishment planning. Develop, test, validate, and deploy predictive models using robust statistical methodologies, including regression analysis, time series ...

Instagram and X! Your New Role... We are looking for the Advanced Analytics Lead who will be responsible for owning, developing and delivering advanced statistical and regression-based analytics that underpin a new measurement solution within the Audiences & Data portfolio. This role sits at the intersection of statistical modelling, insight generation and commercial application. The successful candidate will be the analytical authority on how perception, brand and influence data are modelled, interpreted and translated into robust, defensible insight for clients and internal stakeholders. This is a hands-on senior analytics role, requiring deep expertise in regression ...

documentation Contribute analytical expertise to the development of systemwide policies relating to primary care data quality, coding and reporting Propose and implement changes to statistical, information and managerial policies that enhance analytical processes across the programme Ensure full compliance with information governance, data protection and national reporting standards (e.g. … DCB0129/0160, NHS England data standards). Analytical and Judgement Skills: The post holder will: Provide advanced analytical support using statistical modelling, segmentation, trend analysis and related techniques to inform population health management and improvement Resolve highly complex analytical queries, applying expert judgement where data is limited ...

multiple leading brands and charities helping to transition manual workflows into scalable, automated, production ready systems, building innovative tools which strengthen the marketing mix modelling and econometrics capabilities. What you'll do Maintain and enhance core Python modelling tools for Marketing Effectiveness Migrate manual workflows into automated production … peer code reviews You'll need to have Strong Python engineering skills (clean, modular, production-ready code) Experience in data science, including ML/statistical modelling for MMM and econometrics Strong SQL for data extraction and analysis Solid understanding of software engineering fundamentals (Git, agile workflows) Ability ...

industry Knowledge of time‐value of money concepts, risk return frameworks, asset allocation models highly desirable Good applied statistics skills, such as distributions, statistical testing, regression, etc. Proficiency in using query languages such as SQL desirable Experience with common data science toolkits, such as R desirable Experience with Microsoft … corresponding statistics like K‐means, Bayesian, Clustering Strong technical skills with Python along with NumPy, Pandas, Scikit‐Learn Machine learning experience -> predictive and prescriptive modelling Data wrangling and data cleansing experience Strong analytical skills Any experience with Node.JS would be beneficial. Statistical/mathematical background Business Verticals: Telecom ...

support commercial performance and strategic decision-making. Ensure data accuracy, consistency and integrity across reporting processes. Data Analysis & Commercial Insight Conduct detailed analysis and statistical modelling to identify patterns, trends and anomalies across the business, including but not limited to: Category performance and trend analysis Promotional and campaign … effectiveness Seasonal trend analysis and forecasting Claims trend identification and recommendation of corrective actions Budget modelling and forecasting support Proactive sales performance analysis Private Label performance analysis by market to identify growth opportunities Identification of new business and market opportunities Reporting & Dashboard Development Develop and maintain automated reports ...

every relationship, lead with curiosity, champion diverse perspectives, turn inputs into actions, and uphold trust through integrity. Skills and Competencies Strong expertise in statistical modelling, probability, and numerical methods, required to develop robust catastrophe risk models Proficiency in programming languages such as Python, R, or Julia to build … maintain scalable modelling frameworks Experience analysing climate and atmospheric data, with knowledge of tropical cyclone processes preferred Ability to collaborate effectively in multidisciplinary teams, including use of version control systems (e.g., Git) for shared code development Strong analytical thinking and problem-solving skills to interpret complex hazard behaviours ...

Scientist, Decision Scientist and Product Data Scientist—for upcoming roles where data science genuinely drives decisions. These are roles focused on insight, experimentation and modelling: turning messy real-world data into the understanding and predictions that change what a business does next. You'll work across the full data … science lifecycle—from framing the problem and exploring the data through to modelling, experimentation, communication and measuring impact. The role suits someone who pairs strong statistical and modelling rigour with genuine curiosity about the problem and the storytelling skill to make a result land with the people ...

management, strengthen decision-making, and support transformation objectives. By working closely with stakeholders across Risk, Technology, and the COO, the Data Scientist will integrate modelling, data management, and effective communication to enable evidence-based decisions and foster a data-driven culture within OTCR. Key Responsibilities Data Analysis & Modelling … Conduct in-depth exploratory data analysis to identify trends, patterns, and anomalies across diverse datasets. Develop and deploy predictive models, machine learning algorithms, and statistical techniques, including natural language processing (NLP). Perform quantitative analysis to support scenario testing, stress testing, and thematic risk assessments. Ensure models are explainable ...

producing high-quality outcomes. Responsibilities Deliver data science projects, from problem definition through to actionable insights and presentation of results Develop and apply predictive modelling, supervised and unsupervised machine learning techniques to optimise client operations and business outcomes Build and maintain data pipelines, ensuring data quality, consistency, and integrity … contribution to the enhancement of Sagacity’s data science and analytics product suite Competencies and Experience 2+ years’ experience in data science, analytics, or statistical modelling, ideally with commercial experience within the Telecoms, Banking or Utilities industries; or within a data-related consultancy Educated to degree level (postgraduate ...

community. There is only one Hotspur. Tottenham Hotspur. Role Purpose The Lead Data Scientist is responsible for leading the development and refinement of advanced statistical models and machine learning techniques, creating innovative metrics and diverse insights that enhance the analysis of player and team performance. They will be exploring … analysis, coaching, and the Academy to translate research into on-pitch impact in pursuit of the Clubs ambitious footballing vision. Key Responsibilities Develop advanced statistical and machine learning models to generate innovative metrics and insights from varied and complex data sources, enhancing the understanding of player and team performance. ...

including Residual Value and SMR, Insurance Lease Pricing, Economic Capital, as well as producing the customer pricing. This role sits in the Asset Risk Modelling Team, operating in a matrix management operation, responsible for operating a strong model risk management framework that ensures models are a trusted asset … implemented, operated, enhanced and developed in conjunction with joint ownership for the outcomes and outputs with business SME's. Reporting into the Asset Risk Modelling Manager, the role has the following key responsibilities You will operationalise the model risk management framework in Asset Risk, ensuring model health, reporting, processing ...

Science experience within a commercial environment Strong Python and SQL skills Experience developing and deploying machine learning models into production environments Excellent understanding of statistical modelling, experimentation, and model evaluation Strong feature engineering and exploratory data analysis capabilities Experience communicating technical findings and insights to non-technical stakeholders … learning models to solve real-world business challenges Performing exploratory data analysis, feature engineering, model development, and evaluation Building forecasting, classification, segmentation, and predictive modelling solutions Designing and executing statistical analyses and experiments to support strategic decision-making Translating complex analytical findings into clear recommendations for senior stakeholders ...

outputs clearly to non-technical stakeholders Requirements: Degree in Computer Science, Mathematics, Engineering or a related discipline 2+ years of experience in data analysis, statistical modelling or data science Hands-on experience with Python, R or SQL Proven experience with machine learning algorithms and data science methodologies Familiarity ...

outputs clearly to non-technical stakeholders Requirements: Degree in Computer Science, Mathematics, Engineering or a related discipline 2+ years of experience in data analysis, statistical modelling or data science Hands-on experience with Python, R or SQL Proven experience with machine learning algorithms and data science methodologies Familiarity ...

outputs clearly to non-technical stakeholders Requirements: Degree in Computer Science, Mathematics, Engineering or a related discipline 2+ years of experience in data analysis, statistical modelling or data science Hands-on experience with Python, R or SQL Proven experience with machine learning algorithms and data science methodologies Familiarity ...

outputs clearly to non-technical stakeholders Requirements: Degree in Computer Science, Mathematics, Engineering or a related discipline 2+ years of experience in data analysis, statistical modelling or data science Hands-on experience with Python, R or SQL Proven experience with machine learning algorithms and data science methodologies Familiarity ...

detail. Analytical mindset with the ability to identify trends, patterns, and insights from data. Knowledge of market analysis, business performance analysis, forecasting, or statistical modelling would be beneficial. Familiarity with R, Power BI, Tableau, or other data visualization and analytical tools would be considered an advantage. Good research ...

detail. Analytical mindset with the ability to identify trends, patterns, and insights from data. Knowledge of market analysis, business performance analysis, forecasting, or statistical modelling would be beneficial. Familiarity with R, Power BI, Tableau, or other data visualization and analytical tools would be considered an advantage. Good research ...