126 to 150 of 213 Statistical Modelling Jobs in England

of German credit risk practices and regulation Advanced SQL skills; comfort working with large datasets Analytical mindset and strong communication skills Bonus: experience with Python , credit scoring systems, or statistical modelling 🎯 Why Apply: Join a dynamic, fast-growing fintech with international scale Ownership of high-impact credit initiatives Great benefits, bonus, stock options, and a modern Central London More ❯

of German credit risk practices and regulation Advanced SQL skills; comfort working with large datasets Analytical mindset and strong communication skills Bonus: experience with Python , credit scoring systems, or statistical modelling 🎯 Why Apply: Join a dynamic, fast-growing fintech with international scale Ownership of high-impact credit initiatives Great benefits, bonus, stock options, and a modern Central London More ❯

developing and deploying pipelines, data-lakes, data meshes and other data products Solid experience on understanding, questioning, prioritizing and translating business problems into data solutions (BI, Analytics, deterministic and statistical models, machine learning) Solid experience with Cloud (Azure or AWS) Experience on identifying, gathering and prioritizing Non Functional Requirements, Technical pain points and environment/client constraints Experience on More ❯

developing and deploying pipelines, data-lakes, data meshes and other data products Solid experience on understanding, questioning, prioritizing and translating business problems into data solutions (BI, Analytics, deterministic and statistical models, machine learning) Solid experience with Cloud (Azure or AWS) Experience on identifying, gathering and prioritizing Non Functional Requirements, Technical pain points and environment/client constraints Experience on More ❯

Demonstrable experience working either as a product lead or in a related role, with a track record delivering on a variety of complex data-driven projects. Experience working with statistical models and algorithms. Experience with simulation and analysis tools in the built environment. Ability to research, horizon-scan and validate new ideas and technologies. Self-awareness, an open mind More ❯

contributions in the world of sports analytics. Key responsibilities for the role of Data Scientist include: Collect, clean, and process football-related data from various sources. Develop and implement statistical models and algorithms to analyze player performance and match outcomes. Create detailed reports and visualizations to communicate insights and recommendations to technical and non-technical stakeholders. Collaborate with football … industry experience in a Data Science role and a strong academic background Python Data Science Stack: Advanced proficiency in Python , including pandas , NumPy , scikit-learn , and Jupyter Notebooks . Statistical & ML Modelling: Strong foundation in statistical analysis and proven experience applying a range of machine learning techniques to solve business problems (e.g., regression, classification, clustering, time-series … to non-technical stakeholders. Highly desirable skills include: Football Analytics Domain: Significant plus if experienced with football datasets (event, tracking, etc.) and visualization libraries like mplsoccer . Advanced MLOps & Modelling: Deeper experience with the Vertex AI lifecycle (especially Pipelines ) and advanced modelling techniques relevant to football (player valuation, tactical analysis). Bayesian Modelling: Experience with probabilistic programming More ❯

Primary Details Time Type: Full time Worker Type: Employee Serve as modelling and data science partner for assigned business areas responsible for the scientific integrity of work products, including study design, research methodology, and deployment of statistical approaches and modelling Data Scientist - Fixed term until July 2026 London/Hybrid The Opportunity: Join a high-impact pricing More ❯

through trial and iteration. Youll bring a deep understanding of modern data science and machine learning techniques and know when to apply the right tools, whether thats deep learning, statistical modelling, or classical ML methods. Your toolkit includes Python, SQL, and you're comfortable working in a cloud-first (AWS) ecosystem. Experience with object-oriented programming and packaging More ❯

robust monitoring and alerting systems to maintain data health and accuracy Define KPIs and thresholds in collaboration with technical and non-technical stakeholders Develop and productionise machine learning and statistical models (Python, PySpark) Deploy monitoring solutions on AWS infrastructure Create scalable frameworks for future monitoring needs Investigate anomalies and ensure quick resolution of issues in the data pipeline Advocate More ❯

robust monitoring and alerting systems to maintain data health and accuracy Define KPIs and thresholds in collaboration with technical and non-technical stakeholders Develop and productionise machine learning and statistical models (Python, PySpark) Deploy monitoring solutions on AWS infrastructure Create scalable frameworks for future monitoring needs Investigate anomalies and ensure quick resolution of issues in the data pipeline Advocate More ❯

and compliance strategies. Experience in Enterprise AI Design, focusing on scalable, secure, and cost-effective AI integration. Understanding of data science principles, enabling informed evaluation of machine learning and statistical models. What you'll receive from us: No matter where you may be in your career or personal life, our benefits are designed to add value and support, recognizing More ❯

range of actuarial-related areas. The Role As a Machine Learning Operations Engineer with XPS you will: Model development. Work collaboratively with actuarial analysts to develop machine learning and statistical models to predict outcomes, related to pension schemes, such as life expectancy, default risk, or investment returns. Identify appropriate machine learning algorithms and apply them to enhance predictions, automate … decision-making processes, and improve client offerings. Machine Learning Operations. Responsible for designing, deploying, maintaining and refining statistical and machine learning models using Azure ML. Optimize model performance and computational efficiency. Ensure that applications run smoothly and handle large-scare data efficiently. Implement and maintain monitoring of model drifts, data-quality alerts, scheduled r-training pipelines. Data Management and … quality. Software Development. Write clean, efficient and scalable code in Python. Utilize CI/CD practices for version control, testing and code review. Work closely with actuarial analysts, actuarial modelling team (AMT) and other colleagues in XPS to integrate data science findings into practical advice and strategies. Stay abreast of new trends and technologies in Data Science technologies and More ❯

big data" sources to generate actionable insights. Build databases and is responsible for the curation of Data, including experimental data management. Extracting knowledge, insights and predictions from data using statistical methods, machine learning and data visualization. Work with scientists to identify optimal ways to prepare, annotate, store and navigate their datasets, including data application design and improvement. Define and … Biology, Chemistry, Computer Science, Physics, etc. Relevant work experience in either an academic or industry setting. Working knowledge of cell biology and experience in large scale data analysis and statistical modeling on datasets like RNA-seq, ATAC-seq, protein network, pathways, etc. Proven track record of completed scientific projects as evidenced by publications and preprints. Strong breadth and expertise … in Statistical analysis, machine learning, data visualization, programming (Python, R, etc.), data cleaning and data manipulation. Tools: Python, R, SQL, TensorFlow, Scikit-learn, Tableau, Power BI. Ability to generate high quality ideas and be self-driven to explore. Strong experience in programming and comfortable modifying existing code-base. Experience with Python, R data cleaning and data manipulation or other More ❯

development of new offerings, and deepen our understanding of marketplace dynamics. This role involves advanced data mining and analytics, robust product and data validation, and the development of sophisticated statistical and machine learning-based methodologies. The ideal candidate will have a strong ability to independently research, develop, and maintain high-impact solutions that align Cint’s capabilities with market … and existing products, as well as to understand, analyze, explain, and predict the impact of platform algorithms on clients and partners. Define, establish, and drive the development of advanced statistical and machine learning methods, setting modeling standards and best practices. Conduct exploratory analyses to deepen insights into key metrics and trends, and lead the design and execution of A … equivalent) in Statistics, Quantitative Sciences, Data Science, Operations Research, or a related quantitative field. Strong ability to manipulate, analyze, and interpret large, complex datasets independently. Deep understanding of advanced statistical techniques and concepts (e.g., properties of distributions, hypothesis testing, parametric/non-parametric tests, survey design, sampling theory, experimental design, including multivariate testing, regression/predictive modeling, causal inference More ❯

Data Analysis Position Type Permanent Hours Full Time Result Type Jobs Job Description Summary -Understand complex and critical business problems, formulates integrated analytical approach to mine data sources, employ statistical methods and machine learning algorithms to contribute solving unmet medical needs, discover actionable insights and automate process for reducing effort and time for repeated use. To manage the implementation … science, biostatistics, or other quantitative field (or equivalent). More than 3 years experience in clinical drug development with extensive exposure to clinical trials. Strong knowledge and understanding of statistical methods such as time to event analysis, machine learning, meta-analysis, mixed effect modeling, longitudinal modeling, Bayesian methods, variable selection methods (e.g., lasso, elastic net, random forest), design of … Literacy, Data Management, Data Quality, Data Science, Data Strategy, Data Visualization, Deep Learning, Machine Learning (Ml), Machine Learning Algorithms, Master Data Management, Proteomics, Python (Programming Language), R (Programming Language), Statistical Modeling Create a job alert and receive personalised job recommendations straight to your inbox. #J-18808-Ljbffr More ❯

such as Agentic AI and AI Agents, identifying and developing high-impact use cases from POC to production. Champion best practices in experimentation, causal inference, and uplift modeling, ensuring statistical rigor in decision-making processes. Take ownership of the most complex, high-profile analytical projects, translating ambiguous questions into clear, actionable recommendations that deliver commercial and customer value. Mentor … quantitative role, with a proven track record of supporting and influencing a product organization. Technical & Modeling Expertise: Expert Level proficiency in Python and SQL. Deep, hands-on experience with statistical modeling, (quasi) experimentation, multi-arm bandit, and a wide range of machine learning techniques (e.g., Regression, Classification, Clustering). Product Acumen: Demonstrated ability to define, implement, and operationalize crucial More ❯

and managing comprehensive risk management frameworks for our firm's systematic trading and market making activities. Reporting to the Head of Quantitative Trading, this role combines advanced quantitative risk modelling expertise with deep market knowledge to identify, measure, and mitigate trading risks while optimizing risk-adjusted returns across multiple asset classes and strategies. What you'll do Key Responsibilities … Risk Modelling & Analytics Develop and enhance proprietary risk models for portfolio risk measurement, stress testing, and scenario analysis Research and implement advanced statistical methods for measuring market, credit, liquidity, and operational risks Design and build real-time risk monitoring systems and early warning indicators Collaborate with researchers and developers to translate risk models into production-ready risk management … and implementing successful risk management strategies Experience managing risk across multiple asset classes with expertise in at least two major markets Strong understanding of derivatives pricing, portfolio theory, and statistical risk modelling Technical Skills Expert proficiency in programming languages used in quantitative finance (Python, R, C++, MATLAB, etc.) Deep knowledge of risk management practises , risk approaches Advanced understanding More ❯

core of the challenge is to ideate and deliver a complete portfolio and exposure management capability that leverages Ki's data, algorithm and internal expertise. The product will use statistical modelling techniques, visualisation and workflows to deliver a real time view of Ki's exposure to various natural and non-natural catastrophes across the entirety of our book. … You will be expected to work with the different functions within Ki including Underwriting, Marketing, Operations, Exposure Management and Portfolio Management. You will also need to be comfortable with modelling methodologies and data structures to help make trade-offs and consider options when building the roadmap. Principal Accountabilities: Articulate longer term product direction: Set out the strategic and technical … You’ve applied both theory and practical experience to effectively deliver products, building a versatile toolkit adaptable to diverse situations. You are comfortable talking and understanding technical architecture and statistical techniques, in addition to working directly with customers on how to use the product. You have a strong track record of taking products from concept to successful outcomes, with More ❯

core of the challenge is to ideate and deliver a complete portfolio and exposure management capability that leverages Ki's data, algorithm and internal expertise. The product will use statistical modelling techniques, visualisation and workflows to deliver a real time view of Ki's exposure to various natural and non-natural catastrophes across the entirety of our book. … You will be expected to work with the different functions within Ki including Underwriting, Marketing, Operations, Exposure Management and Portfolio Management. You will also need to be comfortable with modelling methodologies and data structures to help make trade-offs and consider options when building the roadmap. Principal Accountabilities: Articulate longer term product direction: Set out the strategic and technical … You’ve applied both theory and practical experience to effectively deliver products, building a versatile toolkit adaptable to diverse situations. You are comfortable talking and understanding technical architecture and statistical techniques, in addition to working directly with customers on how to use the product. You have a strong track record of taking products from concept to successful outcomes, with 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 ❯

success across multiple geographies. THE ROLE Driving the development of a wide range of credit risk and pricing strategies across the lending book, specifically for the German market Using statistical models and wider analytical tools to drive insight into book performance Wider work on customer analytics and behavioural trends, including work on acquisition and underwriting Close stakeholder interaction and More ❯

success across multiple geographies. THE ROLE Driving the development of a wide range of credit risk and pricing strategies across the lending book, specifically for the German market Using statistical models and wider analytical tools to drive insight into book performance Wider work on customer analytics and behavioural trends, including work on acquisition and underwriting Close stakeholder interaction and More ❯

estate firms understand and act on physical climate risk. You’ll define the ML strategy, shape a high-impact team, and deliver real-world innovation across generative AI, geospatial modelling, and time-series forecasting. Key Responsibilities Own and evolve the company’s AI & ML strategy in line with product and customer priorities Lead, mentor, and grow a high-performing … team of ML Engineers Take prototypes through to production, delivering meaningful product features powered by GenAI and predictive modelling Collaborate with Science and Engineering to integrate ML with physics-based climate models Communicate complex technical concepts in simple, outcome-oriented terms for customers and cross-functional teams Your work will focus on delivering high-value insights and solutions, including … Leveraging satellite imagery and remote sensing for climate hazard detection Enhancing time-series forecasts to inform asset-level risk planning Combining simulation outputs with ML for hybrid physical + statistical modelling What We’re Looking For Proven leadership and strong hands on experience Proven track record of deploying ML into production environments Depth in at least one of More ❯

estate firms understand and act on physical climate risk. You’ll define the ML strategy, shape a high-impact team, and deliver real-world innovation across generative AI, geospatial modelling, and time-series forecasting. Key Responsibilities Own and evolve the company’s AI & ML strategy in line with product and customer priorities Lead, mentor, and grow a high-performing … team of ML Engineers Take prototypes through to production, delivering meaningful product features powered by GenAI and predictive modelling Collaborate with Science and Engineering to integrate ML with physics-based climate models Communicate complex technical concepts in simple, outcome-oriented terms for customers and cross-functional teams Your work will focus on delivering high-value insights and solutions, including … Leveraging satellite imagery and remote sensing for climate hazard detection Enhancing time-series forecasts to inform asset-level risk planning Combining simulation outputs with ML for hybrid physical + statistical modelling What We’re Looking For Proven leadership and strong hands on experience Proven track record of deploying ML into production environments Depth in at least one of More ❯