1 to 25 of 108 Statistical Modelling Jobs in the South East

in London. They work locally but operate Globally with offices across the globe. A Senior Sports Quantitative Modeller is a senior individual contributor and an expert in mathematical and statistical modelling, specifically for sports betting. This role is responsible for deriving new markets, understanding complex statistical distributions, and building robust, accurate quantitative models, particularly for Bet Builder … conception to deployment, and providing technical guidance to junior modellers. This role reports directly to the Data Science Manager and is an integral part of our Data Science - Core Modelling function. Key Responsibilities: Design, develop, and implement advanced mathematical and statistical models for sports betting, with a primary focus on deriving new markets and enhancing existing offerings. Possess … a deep understanding of complex statistical distributions and leverage techniques such as Monte Carlo simulations in model development. Rigorously back test and validate models to ensure their robustness, accuracy, and profitability in real-world betting scenarios. Drive and lead quantitative modelling initiatives, with a particular focus on BetBuilder products, from initial concept through to production deployment. Operate with More ❯

in London. They work locally but operate Globally with offices across the globe. A Senior Sports Quantitative Modeller is a senior individual contributor and an expert in mathematical and statistical modelling, specifically for sports betting. This role is responsible for deriving new markets, understanding complex statistical distributions, and building robust, accurate quantitative models, particularly for Bet Builder … conception to deployment, and providing technical guidance to junior modellers. This role reports directly to the Data Science Manager and is an integral part of our Data Science - Core Modelling function. Key Responsibilities: Design, develop, and implement advanced mathematical and statistical models for sports betting, with a primary focus on deriving new markets and enhancing existing offerings. Possess … a deep understanding of complex statistical distributions and leverage techniques such as Monte Carlo simulations in model development. Rigorously back test and validate models to ensure their robustness, accuracy, and profitability in real-world betting scenarios. Drive and lead quantitative modelling initiatives, with a particular focus on BetBuilder products, from initial concept through to production deployment. Operate with More ❯

in London. They work locally but operate Globally with offices across the globe. A Senior Sports Quantitative Modeller is a senior individual contributor and an expert in mathematical and statistical modelling, specifically for sports betting. This role is responsible for deriving new markets, understanding complex statistical distributions, and building robust, accurate quantitative models, particularly for Bet Builder … conception to deployment, and providing technical guidance to junior modellers. This role reports directly to the Data Science Manager and is an integral part of our Data Science - Core Modelling function. Key Responsibilities: Design, develop, and implement advanced mathematical and statistical models for sports betting, with a primary focus on deriving new markets and enhancing existing offerings. Possess … a deep understanding of complex statistical distributions and leverage techniques such as Monte Carlo simulations in model development. Rigorously back test and validate models to ensure their robustness, accuracy, and profitability in real-world betting scenarios. Drive and lead quantitative modelling initiatives, with a particular focus on BetBuilder products, from initial concept through to production deployment. Operate with More ❯

in London. They work locally but operate Globally with offices across the globe. A Senior Sports Quantitative Modeller is a senior individual contributor and an expert in mathematical and statistical modelling, specifically for sports betting. This role is responsible for deriving new markets, understanding complex statistical distributions, and building robust, accurate quantitative models, particularly for Bet Builder … conception to deployment, and providing technical guidance to junior modellers. This role reports directly to the Data Science Manager and is an integral part of our Data Science - Core Modelling function. Key Responsibilities: Design, develop, and implement advanced mathematical and statistical models for sports betting, with a primary focus on deriving new markets and enhancing existing offerings. Possess … a deep understanding of complex statistical distributions and leverage techniques such as Monte Carlo simulations in model development. Rigorously back test and validate models to ensure their robustness, accuracy, and profitability in real-world betting scenarios. Drive and lead quantitative modelling initiatives, with a particular focus on BetBuilder products, from initial concept through to production deployment. Operate with More ❯

Data Scientist with PyMc & Marketing Mixed Modelling experience 6 Months Contract Inside IR35 Remote/1 day onsite a month Bankside My client a top Global company are currently looking to recruit a Data Scientist with PyMc & MMM experience to join their team on a 6-month contract basis. Please note if successful this position will need to set … up via an Umbrella Company/PAYE. This Senior Data scientist required to work with our clients Data Science team to drive Marketing Effectiveness using Marketing Mix Modelling, Multi-Touch Attribution, and other models. Responsibilities: Oversee and be responsible for data collection including data extraction and manipulation, data analysis and validation. Analyse all datasets to ensure that each KPI … Requirements: Proven experience in developing and implementing Marketing Mix Models Be an expert in PyMc, Python and familiar with R programming for MMM Models Have in depth understanding of statistical modelling/ML techniques Experience with Regression based models applied to the context of MMM modelling Solid experience with Probabilistic Programming and Bayesian Methods Be an expert More ❯

in London. We are looking for an AI analytics engineer/data focused developer. You’ll join our London office to drive development of Savantiq’s analytics capabilities: from statistical modelling and custom ML models, to retrieval systems and fine-tuned LLMs. You’ll work directly with the CTO, shaping cutting-edge tools that transform deal-making in … seeking the right candidate, with c. 2-4 years of experience, to strengthen our position even further. The role is in person in London. Skills Core Solid foundation in statistical modelling and data-driven problem solving, with hands-on experience with a range of ML/AI techniques, e.g. supervised/unsupervised learning, natural language processing and LLMs. More ❯

in London. We are looking for an AI analytics engineer/data focused developer. You’ll join our London office to drive development of Savantiq’s analytics capabilities: from statistical modelling and custom ML models, to retrieval systems and fine-tuned LLMs. You’ll work directly with the CTO, shaping cutting-edge tools that transform deal-making in … seeking the right candidate, with c. 2-4 years of experience, to strengthen our position even further. The role is in person in London. Skills Core Solid foundation in statistical modelling and data-driven problem solving, with hands-on experience with a range of ML/AI techniques, e.g. supervised/unsupervised learning, natural language processing and LLMs. More ❯

analysis SQL for querying and manipulation of structured customer and campaign data (mandatory) MS Excel including pivot tables, VLOOKUP, Power Query (mandatory) Python or R for advanced data manipulation, statistical analysis and modelling (mandatory) Data visualisation Power BI and/or Looker Studio for creating dynamic dashboards and reports in context of marketing KPIs (mandatory) Forecasting, modelling and predictive analytics (highly desirable) Predictive/statistical modelling Time series analysis Forecasting marketing metrics such as response, conversion and churn rate using historical campaign data Data-driven business casing and budgeting Marketing performance (mandatory) Good knowledge of forecasting techniques, marketing performance/channel metrics, and KPI frameworks and targets Campaign planning and forecasting Campaign evaluation with … discipline Professional certifications in data analytics, forecasting, or marketing analytics (e.g., Google Analytics, Microsoft Power BI, Tableau, CIM, or similar) (highly desirable) Familiarity with tools or languages used for statistical forecasting (e.g., R, Python More ❯

analysis SQL for querying and manipulation of structured customer and campaign data (mandatory) MS Excel including pivot tables, VLOOKUP, Power Query (mandatory) Python or R for advanced data manipulation, statistical analysis and modelling (mandatory) Data visualisation Power BI and/or Looker Studio for creating dynamic dashboards and reports in context of marketing KPIs (mandatory) Forecasting, modelling and predictive analytics (highly desirable) Predictive/statistical modelling Time series analysis Forecasting marketing metrics such as response, conversion and churn rate using historical campaign data Data-driven business casing and budgeting Marketing performance (mandatory) Good knowledge of forecasting techniques, marketing performance/channel metrics, and KPI frameworks and targets Campaign planning and forecasting Campaign evaluation with … discipline Professional certifications in data analytics, forecasting, or marketing analytics (e.g., Google Analytics, Microsoft Power BI, Tableau, CIM, or similar) (highly desirable) Familiarity with tools or languages used for statistical forecasting (e.g., R, Python More ❯

analysis SQL for querying and manipulation of structured customer and campaign data (mandatory) MS Excel including pivot tables, VLOOKUP, Power Query (mandatory) Python or R for advanced data manipulation, statistical analysis and modelling (mandatory) Data visualisation Power BI and/or Looker Studio for creating dynamic dashboards and reports in context of marketing KPIs (mandatory) Forecasting, modelling and predictive analytics (highly desirable) Predictive/statistical modelling Time series analysis Forecasting marketing metrics such as response, conversion and churn rate using historical campaign data Data-driven business casing and budgeting Marketing performance (mandatory) Good knowledge of forecasting techniques, marketing performance/channel metrics, and KPI frameworks and targets Campaign planning and forecasting Campaign evaluation with … discipline Professional certifications in data analytics, forecasting, or marketing analytics (e.g., Google Analytics, Microsoft Power BI, Tableau, CIM, or similar) (highly desirable) Familiarity with tools or languages used for statistical forecasting (e.g., R, Python More ❯

working with one of the most exciting and rich retail data sets in the UK. You'll play a pivotal role in driving commercial finance value through advanced analytics, statistical modelling, and data storytelling. In a dynamic and collaborative environment, you'll support data-driven decisions across the business. We're committed to continuous learning and development, so … key role in unlocking value from complex financial data, partnering closely with Finance Managers and senior stakeholders to deliver advanced analytical projects from end to end. You'll apply statistical techniques such as regression analysis, time series modelling, and hypothesis testing to uncover trends, forecast outcomes, and solve business challenges. Your insights will drive strategic decisions, and you … levels up to director-level and thrive in a collaborative environment. Essential Criteria Educational degree in Mathematics, Statistics, Data Science, or a related analytical field is desirable Experience applying statistical techniques and modelling in a commercial setting (such as regression analysis, time series forecasting and hypothesis testing). Exposure to machine learning methods, including supervised and unsupervised learning More ❯

strategy, and optimise commercial performance. This is a high-impact role for a proactive, solutions-oriented professional who can prioritise based on business needs. Key Responsibilities: Deliver analytics and statistical modelling to shape commercial strategy and support measurable business outcomes. Prepare sales and product forecasts, including OTE projections, to aid planning and resource allocation. Track, analyse, and report … like you to have: 37 years of experience in data analytics, business intelligence, or commercial analysis. Strong proficiency in Excel and experience with BI platforms (Power BI, Tableau) and statistical modeling. Ability to translate data insights into actionable recommendations for sales, finance, and product teams. Commercial awareness, analytical mindset, and strong problem-solving skills. Excellent communication and stakeholder management More ❯

strong plus. Experience Required skills Hands-on experience building and deploying ML models in Python SQL skills and familiarity with AWS for deployment and data workflows. Strong knowledge of statistical modelling, anomaly detection, clustering, and supervised/unsupervised learning Experience working with large-scale data Proven success collaborating with product and engineering teams to ship ML-based features More ❯

strong plus. Experience Required skills Hands-on experience building and deploying ML models in Python SQL skills and familiarity with AWS for deployment and data workflows. Strong knowledge of statistical modelling, anomaly detection, clustering, and supervised/unsupervised learning Experience working with large-scale data Proven success collaborating with product and engineering teams to ship ML-based features More ❯

strong plus. Experience Required skills Hands-on experience building and deploying ML models in Python SQL skills and familiarity with AWS for deployment and data workflows. Strong knowledge of statistical modelling, anomaly detection, clustering, and supervised/unsupervised learning Experience working with large-scale data Proven success collaborating with product and engineering teams to ship ML-based features More ❯

strong plus. Experience Required skills Hands-on experience building and deploying ML models in Python SQL skills and familiarity with AWS for deployment and data workflows. Strong knowledge of statistical modelling, anomaly detection, clustering, and supervised/unsupervised learning Experience working with large-scale data Proven success collaborating with product and engineering teams to ship ML-based features More ❯

Senior Data Scientist - Asset Risk Modelling London - Hybrid, 3 days in office£85,000 - £90,000 + Bonus + Great Pension + Private Healthcare + 28 days Holiday + Hybrid Working This is a brilliant opportunity for a Senior Data Scientist with strong experience in model risk management, pricing, and insurance to join a market-leading organisation during a … SMR, Insurance Lease Pricing, Economic Capital, and Customer Pricing. As part of their continued expansion, they are now seeking a talented Senior Data Scientist to join the Asset Risk Modelling Team and help shape the future of their modelling capabilities.In this role, you will take ownership of developing, maintaining, and enhancing advanced forecasting and pricing models that underpin … critical business decisions. Working closely with the Modelling Manager and wider stakeholders, you'll ensure the robustness and transparency of all models, while continuously improving methodologies, data use, and analytical processes. You will also play a key role in delivering the model risk management framework across the Asset Risk function.The ideal candidate will be an experienced Data Scientist/ More ❯

a Data Scientist, you'll sit within the underwriting data science team, helping to develop and deploy high-impact climate and natural catastrophe models. Key Responsibilities Design and enhance statistical models and ML algorithms to better forecast weather and natural hazard risks (wildfires, hail, tsunamis, etc.) Build performant, scalable tools to price and monitor risk in real-world environments … Translate client needs into technical modelling improvements alongside commercial colleagues Contribute to the development of the company's internal platform and tooling Participate in R&D sessions and technical discussions to ensure continued innovation Take on technical responsibility for model performance, accuracy, and deployment Collaborate with a diverse team across underwriting, product, and engineering Requirements Master's degree in … computer science, statistics, applied mathematics, or a related discipline Prior experience (internship or full-time) in data science or climate risk modelling Strong grasp of statistical modelling and machine learning techniques Proficiency in Python and common ML libraries (e.g. scikit-learn) Curious, pragmatic, and driven to solve real-world problems with high social impact Passionate about the More ❯

a Data Scientist, you’ll sit within the underwriting data science team, helping to develop and deploy high-impact climate and natural catastrophe models. Key Responsibilities Design and enhance statistical models and ML algorithms to better forecast weather and natural hazard risks (wildfires, hail, tsunamis, etc.) Build performant, scalable tools to price and monitor risk in real-world environments … Translate client needs into technical modelling improvements alongside commercial colleagues Contribute to the development of the company’s internal platform and tooling Participate in R&D sessions and technical discussions to ensure continued innovation Take on technical responsibility for model performance, accuracy, and deployment Collaborate with a diverse team across underwriting, product, and engineering Requirements Master’s degree in … computer science, statistics, applied mathematics, or a related discipline Prior experience (internship or full-time) in data science or climate risk modelling Strong grasp of statistical modelling and machine learning techniques Proficiency in Python and common ML libraries (e.g. scikit-learn) Curious, pragmatic, and driven to solve real-world problems with high social impact Passionate about the More ❯

a Data Scientist, you’ll sit within the underwriting data science team, helping to develop and deploy high-impact climate and natural catastrophe models. Key Responsibilities Design and enhance statistical models and ML algorithms to better forecast weather and natural hazard risks (wildfires, hail, tsunamis, etc.) Build performant, scalable tools to price and monitor risk in real-world environments … Translate client needs into technical modelling improvements alongside commercial colleagues Contribute to the development of the company’s internal platform and tooling Participate in R&D sessions and technical discussions to ensure continued innovation Take on technical responsibility for model performance, accuracy, and deployment Collaborate with a diverse team across underwriting, product, and engineering Requirements Master’s degree in … computer science, statistics, applied mathematics, or a related discipline Prior experience (internship or full-time) in data science or climate risk modelling Strong grasp of statistical modelling and machine learning techniques Proficiency in Python and common ML libraries (e.g. scikit-learn) Curious, pragmatic, and driven to solve real-world problems with high social impact Passionate about the More ❯

a Data Scientist, you’ll sit within the underwriting data science team, helping to develop and deploy high-impact climate and natural catastrophe models. Key Responsibilities Design and enhance statistical models and ML algorithms to better forecast weather and natural hazard risks (wildfires, hail, tsunamis, etc.) Build performant, scalable tools to price and monitor risk in real-world environments … Translate client needs into technical modelling improvements alongside commercial colleagues Contribute to the development of the company’s internal platform and tooling Participate in R&D sessions and technical discussions to ensure continued innovation Take on technical responsibility for model performance, accuracy, and deployment Collaborate with a diverse team across underwriting, product, and engineering Requirements Master’s degree in … computer science, statistics, applied mathematics, or a related discipline Prior experience (internship or full-time) in data science or climate risk modelling Strong grasp of statistical modelling and machine learning techniques Proficiency in Python and common ML libraries (e.g. scikit-learn) Curious, pragmatic, and driven to solve real-world problems with high social impact Passionate about the More ❯

Engineer , Data Scientist , or similar role. Strong programming skills in Python (experience with libraries such as TensorFlow, PyTorch, scikit-learn, pandas, NumPy). Solid understanding of machine learning algorithms , statistical modelling , and deep learning architectures . Hands-on experience with MLOps tools and frameworks (e.g., MLflow, Kubeflow, SageMaker, Vertex AI). Experience with data engineering concepts — ETL pipelines More ❯

Engineer , Data Scientist , or similar role. Strong programming skills in Python (experience with libraries such as TensorFlow, PyTorch, scikit-learn, pandas, NumPy). Solid understanding of machine learning algorithms , statistical modelling , and deep learning architectures . Hands-on experience with MLOps tools and frameworks (e.g., MLflow, Kubeflow, SageMaker, Vertex AI). Experience with data engineering concepts — ETL pipelines More ❯

Engineer , Data Scientist , or similar role. Strong programming skills in Python (experience with libraries such as TensorFlow, PyTorch, scikit-learn, pandas, NumPy). Solid understanding of machine learning algorithms , statistical modelling , and deep learning architectures . Hands-on experience with MLOps tools and frameworks (e.g., MLflow, Kubeflow, SageMaker, Vertex AI). Experience with data engineering concepts — ETL pipelines More ❯

career the that of a Data Scientist. This builds on the knowledge of the Data+ certification and enables you to demonstrate your knowledge in advanced data processing, cleaning, and statistical modelling concepts. You will demonstrate your knowledge of machine learning, industry trends and use of specialised data science applications. You will also apply mathematical and statistical methods More ❯