76 to 99 of 99 Statistical Modelling Jobs in the UK excluding London

advanced research. The firm designs and deploys sophisticated trading strategies across, L/S equities, systematic, and global macro. Their success is built on solving complex challenges through advanced statistical modelling, machine learning, and the intelligent use of vast datasets. With AUM over $35bn and a culture that thrives on innovation, collaboration, and intellectual curiosity, this is the More ❯

across the business. Develop, improve, and maintain customer segmentation models to provide deep insights into the subscription base and inform Product/Marketing strategies. Utilise predictive analytics and retention modelling to forecast churn risk and customer behaviour, leveraging data science techniques. Collaborate with cross-functional teams , including marketing, finance, product and editorial, to ensure data-driven decision-making aligns … analytics, preferably in a subscription-based business . Strong commercial acumen , with the ability to translate data insights into business strategies. Advanced analytical and quantitative skills , with expertise in statistical analysis and predictive modeling. Proficiency in SQL, Python, or R , and experience with data visualization tools such as Power BI, Tableau, or Looker Studio. Excellent stakeholder management skills , with … Knowledge of data science and machine learning techniques applied to subscription-based businesses, including churn prediction and lifetime value modeling. Experience in customer segmentation, cohort analysis, and marketing mix modelling (MMM). Example projects The i Paper - POLARIS Dashboard build and automation, including the setting of the KPI's - which we settled on using the last 12 months averages. More ❯

across the business. Develop, improve, and maintain customer segmentation models to provide deep insights into the subscription base and inform Product/Marketing strategies. Utilise predictive analytics and retention modelling to forecast churn risk and customer behaviour, leveraging data science techniques. Collaborate with cross-functional teams , including marketing, finance, product and editorial, to ensure data-driven decision-making aligns … analytics, preferably in a subscription-based business . Strong commercial acumen , with the ability to translate data insights into business strategies. Advanced analytical and quantitative skills , with expertise in statistical analysis and predictive modeling. Proficiency in SQL, Python, or R , and experience with data visualization tools such as Power BI, Tableau, or Looker Studio. Excellent stakeholder management skills , with … Knowledge of data science and machine learning techniques applied to subscription-based businesses, including churn prediction and lifetime value modeling. Experience in customer segmentation, cohort analysis, and marketing mix modelling (MMM). Example projects The i Paper - POLARIS Dashboard build and automation, including the setting of the KPI's - which we settled on using the last 12 months averages. More ❯

across the business. Develop, improve, and maintain customer segmentation models to provide deep insights into the subscription base and inform Product/Marketing strategies. Utilise predictive analytics and retention modelling to forecast churn risk and customer behaviour, leveraging data science techniques. Collaborate with cross-functional teams , including marketing, finance, product and editorial, to ensure data-driven decision-making aligns … analytics, preferably in a subscription-based business . Strong commercial acumen , with the ability to translate data insights into business strategies. Advanced analytical and quantitative skills , with expertise in statistical analysis and predictive modeling. Proficiency in SQL, Python, or R , and experience with data visualization tools such as Power BI, Tableau, or Looker Studio. Excellent stakeholder management skills , with … Knowledge of data science and machine learning techniques applied to subscription-based businesses, including churn prediction and lifetime value modeling. Experience in customer segmentation, cohort analysis, and marketing mix modelling (MMM). Example projects The i Paper - POLARIS Dashboard build and automation, including the setting of the KPI's - which we settled on using the last 12 months averages. More ❯

that NHS Wales Performance and Improvement delivers its objectives Your day-to-day role will require you to have a vast array of skills in areas including analytical, advanced statistical techniques, dashboard and information flow development, people and project management and negotiation and communication in order to deliver high-profile projects to meet the team's objectives. Where applicable … of providing and presenting highly complex information to clinicians and senior managers. Experience of using business intelligence tools to provide meaningful insight to a range of audiences. Experience of statistical analysis and mathematical modelling of highly complex information. Experience of using cloud computing platforms, such as Google Cloud Platform. Skills Advanced IT and analytical skills with an in … depth knowledge of IT tools/systems such as SQL, business intelligence systems such as Power BI, statistical software such as R, and programming languages such as Python. Knowledge Excellent knowledge of NHS services and information systems Knowledge of the concepts of demand and capacity modelling and its application to health service planning. Advanced statistical and mathematical More ❯

fan engagement. If you're passionate about using advanced data science to drive real-world impact in sport, this is the role for you. Key Responsibilities Develop and apply statistical models and algorithms to analyse player performance, match outcomes, and tactical insights Collect, clean, and process football-related data from diverse sources Build clear, compelling visualizations and deliver insights … Background 3+ years of industry experience as a Data Scientist , plus a strong academic foundation Python Data Science Stack : Advanced proficiency in Python , including Pandas, NumPy and scikit-learn. Statistical & Machine Learning Modelling : Experience with a variety of ML techniques ( regression, classification, clustering, time-series forecasting ) Experience with deep learning frameworks such as Keras or PyTorch Model Deployment … into actionable insights for coaches, analysts, and execs Highly Desirable Skills Football Analytics Experience : Familiarity with football-specific datasets (event, tracking, positiona l), and libraries like mplsoccer Advanced MLOps & Modelling : Experience with the Vertex AI ecosystem, especially pipelines, and advanced techniques such as player valuation , tactical modelling , etc. Bayesian Modelling : Knowledge of probabilistic programming (e.g., PyMC ) for More ❯

fan engagement. If you're passionate about using advanced data science to drive real-world impact in sport, this is the role for you. Key Responsibilities Develop and apply statistical models and algorithms to analyse player performance, match outcomes, and tactical insights Collect, clean, and process football-related data from diverse sources Build clear, compelling visualizations and deliver insights … Background 3+ years of industry experience as a Data Scientist , plus a strong academic foundation Python Data Science Stack : Advanced proficiency in Python , including Pandas, NumPy and scikit-learn. Statistical & Machine Learning Modelling : Experience with a variety of ML techniques ( regression, classification, clustering, time-series forecasting ) Experience with deep learning frameworks such as Keras or PyTorch Model Deployment … into actionable insights for coaches, analysts, and execs Highly Desirable Skills Football Analytics Experience : Familiarity with football-specific datasets (event, tracking, positiona l), and libraries like mplsoccer Advanced MLOps & Modelling : Experience with the Vertex AI ecosystem, especially pipelines, and advanced techniques such as player valuation , tactical modelling , etc. Bayesian Modelling : Knowledge of probabilistic programming (e.g., PyMC ) for More ❯

fan engagement. If you're passionate about using advanced data science to drive real-world impact in sport, this is the role for you. Key Responsibilities Develop and apply statistical models and algorithms to analyse player performance, match outcomes, and tactical insights Collect, clean, and process football-related data from diverse sources Build clear, compelling visualizations and deliver insights … Background 3+ years of industry experience as a Data Scientist , plus a strong academic foundation Python Data Science Stack : Advanced proficiency in Python , including Pandas, NumPy and scikit-learn. Statistical & Machine Learning Modelling : Experience with a variety of ML techniques ( regression, classification, clustering, time-series forecasting ) Experience with deep learning frameworks such as Keras or PyTorch Model Deployment … into actionable insights for coaches, analysts, and execs Highly Desirable Skills Football Analytics Experience : Familiarity with football-specific datasets (event, tracking, positiona l), and libraries like mplsoccer Advanced MLOps & Modelling : Experience with the Vertex AI ecosystem, especially pipelines, and advanced techniques such as player valuation , tactical modelling , etc. Bayesian Modelling : Knowledge of probabilistic programming (e.g., PyMC ) for More ❯

SKILLS REQUIRED Microsoft Dynamics Business Central Microsoft Power BI Microsoft Excel advanced user SAP Business Objects Excellent communication and interpretation skills Excellent numerical and analytical skills Knowledge of advanced statistical models, graphs and databases The ability to interpret data and offer recommendations based on that interpretation. Proficiency in computer programs and data analysis tools Ability to distinguish between reliable More ❯

SKILLS REQUIRED Microsoft Dynamics Business Central Microsoft Power BI Microsoft Excel advanced user SAP Business Objects Excellent communication and interpretation skills Excellent numerical and analytical skills Knowledge of advanced statistical models, graphs and databases The ability to interpret data and offer recommendations based on that interpretation. Proficiency in computer programs and data analysis tools Ability to distinguish between reliable More ❯

SKILLS REQUIRED Microsoft Dynamics Business Central Microsoft Power BI Microsoft Excel advanced user SAP Business Objects Excellent communication and interpretation skills Excellent numerical and analytical skills Knowledge of advanced statistical models, graphs and databases The ability to interpret data and offer recommendations based on that interpretation. Proficiency in computer programs and data analysis tools Ability to distinguish between reliable More ❯

23. The ideal candidate will have a strong quantitative background, hands-on programming experience in Python, and a track record of developing or validating AI/machine learning or statistical models in surveillance or conduct risk contexts. Key Responsibilities Independently validate and periodically review trade surveillance models for robustness and regulatory compliance Evaluate data quality, feature engineering, and model … performance across surveillance systems Review model documentation for conceptual soundness, implementation quality, and governance controls Conduct benchmarking, backtesting, and stress testing using Python to challenge model design Assess statistical and machine learning-based surveillance systems for transparency and effective alert thresholds Provide quantitative and qualitative assessments of model accuracy, stability, and business suitability Collaborate with model developers, compliance, and More ❯

Duties and responsibilities will include: Mining data from a variety of company databases and systems Preparation of data for analysis Data analysis and interpretation, identifying patterns and potential insights Statistical modeling and using machine learning techniques to identify trends and make forecasts Evaluating model performance using different metrics and refining models to improve performance Create visual representation of data … Masters degree in data science, applied data science or related field preferred Experienced with database systems, SQL and full proficiency in Power BI Mathematically minded with solid knowledge of statistical methods and probability Experienced with various machine learning algorithms and frameworks Analytical with a sound problem solving ability Task orientated with a solid sense of urgency Excellent communication skills More ❯

Manager , where you'll lead the development of advanced pricing models and strategies across key personal lines products. The Opportunity In this pivotal role, you'll take ownership of statistical risk modelling and pricing frameworks for products including Private Car, Van, Bike, and Household . Working closely with expert teams across pricing, underwriting, and data science, you'll … strategic decisions that drive both profitability and market competitiveness . This is a brilliant role for a technically strong, commercially minded pricing specialist who wants to combine hands-on modelling with strategic influence in a business that values innovation, collaboration, and continuous improvement. Key Responsibilities Lead the design, development, and refinement of pricing models and risk segmentation frameworks across … multiple personal lines portfolios. Apply statistical and machine learning techniques to identify performance trends, insights, and opportunities for optimisation. Support the execution of pricing and underwriting strategies that balance growth, retention, and profitability. Deliver clear, actionable insights and present recommendations to senior stakeholders across pricing, underwriting, and finance. Champion innovation by identifying and implementing enhancements to models, tools, data More ❯

strategies and predictive modelling. You'll work closely with cross-functional teams to build tools and insights that support effective risk mitigation and informed decision-making. Key Responsibilities: Develop statistical and machine learning models to simulate risk scenarios. Analyse large datasets to uncover trends and emerging risks. Translate insights into actionable risk mitigation strategies. Build dashboards and visualisations for … clean, integrated data. Continuously refine models to adapt to evolving risk landscapes. Requirements: Experience as a data scientist. Strong Python and SQL skills. Experience with machine learning frameworks and statistical analysis. Knowledge of LLMs and AI modelling tools. Excellent communication and problem-solving skills. Comfortable working in a fast-paced, collaborative environment. Benefits: Salary up to More ❯

strategies and predictive modelling. You'll work closely with cross-functional teams to build tools and insights that support effective risk mitigation and informed decision-making. Key Responsibilities: Develop statistical and machine learning models to simulate risk scenarios. Analyse large datasets to uncover trends and emerging risks. Translate insights into actionable risk mitigation strategies. Build dashboards and visualisations for … clean, integrated data. Continuously refine models to adapt to evolving risk landscapes. Requirements: Experience as a data scientist. Strong Python and SQL skills. Experience with machine learning frameworks and statistical analysis. Knowledge of LLMs and AI modelling tools. Excellent communication and problem-solving skills. Comfortable working in a fast-paced, collaborative environment. Benefits: Salary up to More ❯

strategies and predictive modelling. You'll work closely with cross-functional teams to build tools and insights that support effective risk mitigation and informed decision-making. Key Responsibilities: Develop statistical and machine learning models to simulate risk scenarios. Analyse large datasets to uncover trends and emerging risks. Translate insights into actionable risk mitigation strategies. Build dashboards and visualisations for … clean, integrated data. Continuously refine models to adapt to evolving risk landscapes. Requirements: Experience as a data scientist. Strong Python and SQL skills. Experience with machine learning frameworks and statistical analysis. Knowledge of LLMs and AI modelling tools. Excellent communication and problem-solving skills. Comfortable working in a fast-paced, collaborative environment. Benefits: Salary up to More ❯

strategies and predictive modelling. You'll work closely with cross-functional teams to build tools and insights that support effective risk mitigation and informed decision-making. Key Responsibilities: Develop statistical and machine learning models to simulate risk scenarios. Analyse large datasets to uncover trends and emerging risks. Translate insights into actionable risk mitigation strategies. Build dashboards and visualisations for … clean, integrated data. Continuously refine models to adapt to evolving risk landscapes. Requirements: Experience as a data scientist. Strong Python and SQL skills. Experience with machine learning frameworks and statistical analysis. Knowledge of LLMs and AI modelling tools. Excellent communication and problem-solving skills. Comfortable working in a fast-paced, collaborative environment. Benefits: Salary up to More ❯

strategies and predictive modelling. You'll work closely with cross-functional teams to build tools and insights that support effective risk mitigation and informed decision-making. Key Responsibilities: Develop statistical and machine learning models to simulate risk scenarios. Analyse large datasets to uncover trends and emerging risks. Translate insights into actionable risk mitigation strategies. Build dashboards and visualisations for … clean, integrated data. Continuously refine models to adapt to evolving risk landscapes. Requirements: Experience as a data scientist. Strong Python and SQL skills. Experience with machine learning frameworks and statistical analysis. Knowledge of LLMs and AI modelling tools. Excellent communication and problem-solving skills. Comfortable working in a fast-paced, collaborative environment. Benefits: Salary up to More ❯

strategies and predictive modelling. You'll work closely with cross-functional teams to build tools and insights that support effective risk mitigation and informed decision-making. Key Responsibilities: Develop statistical and machine learning models to simulate risk scenarios. Analyse large datasets to uncover trends and emerging risks. Translate insights into actionable risk mitigation strategies. Build dashboards and visualisations for … clean, integrated data. Continuously refine models to adapt to evolving risk landscapes. Requirements: Experience as a data scientist. Strong Python and SQL skills. Experience with machine learning frameworks and statistical analysis. Knowledge of LLMs and AI modelling tools. Excellent communication and problem-solving skills. Comfortable working in a fast-paced, collaborative environment. Benefits: Salary up to More ❯

strategies and predictive modelling. You'll work closely with cross-functional teams to build tools and insights that support effective risk mitigation and informed decision-making. Key Responsibilities: Develop statistical and machine learning models to simulate risk scenarios. Analyse large datasets to uncover trends and emerging risks. Translate insights into actionable risk mitigation strategies. Build dashboards and visualisations for … clean, integrated data. Continuously refine models to adapt to evolving risk landscapes. Requirements: Experience as a data scientist. Strong Python and SQL skills. Experience with machine learning frameworks and statistical analysis. Knowledge of LLMs and AI modelling tools. Excellent communication and problem-solving skills. Comfortable working in a fast-paced, collaborative environment. Benefits: Salary up to More ❯

strategies and predictive modelling. You'll work closely with cross-functional teams to build tools and insights that support effective risk mitigation and informed decision-making. Key Responsibilities: Develop statistical and machine learning models to simulate risk scenarios. Analyse large datasets to uncover trends and emerging risks. Translate insights into actionable risk mitigation strategies. Build dashboards and visualisations for … clean, integrated data. Continuously refine models to adapt to evolving risk landscapes. Requirements: Experience as a data scientist. Strong Python and SQL skills. Experience with machine learning frameworks and statistical analysis. Knowledge of LLMs and AI modelling tools. Excellent communication and problem-solving skills. Comfortable working in a fast-paced, collaborative environment. Benefits: Salary up to More ❯

with the Head of Analytics to deliver actionable insights across the network of charging points Analyse customer behaviour, usage patterns, and operational data to inform strategy and growth Build statistical models for segmentation, regression, predictive modelling, and forecasting Support pricing and revenue optimisation initiatives, including dynamic pricing strategies Query and process large datasets coming from multiple real-time … sources Translate complex analysis into clear recommendations for non-technical stakeholders What You'll Need: Strong SQL and Python skills; experience in AWS environments is a plus Solid statistical analysis background (segmentation, regression, forecasting) Hands-on, adaptable, and comfortable in a smaller, fast-moving team environment Excellent communication skills and ability to take ownership of projects Experience delivering actionable More ❯

Quantitative Analyst required by a sports trading company based in central London. The company have been established for more than 10 years, successfully developing statistical models and analytical frameworks. The successful Quantitative Analyst will work within the prediction team, using extensive datasets to enhance existing predictive models as well as researching new methods. The role will be working alongside … a team of Quants, Developers, and Analysts. Due to the nature of the business this is mainly an office-based role. Experience required: 3+ years' experience within predictive modelling, machine learning, and probability theory. Ideally this would be within sports or gaming/betting industries. Understanding of techniques such as Monte Carlo simulation, Bayesian modelling, GLMs, mixed effects More ❯