151 to 175 of 667 Model Validation Jobs in the UK

or wastage risks. Build and iterate on AI-powered decision support tools to optimize inventory management and buying policies. Design and execute experiments (A/B tests) to validate model performance and drive improvements in stock ordering strategies. Collaborate with Category and In-Stock teams to evolve the Stock Ordering Tool using intelligent algorithms and real-time data. Analyze … as Mathematics, Statistics, Computer Science, Data Science, or Engineering. Benefits: Comprehensive medical and dental insurance. Equity participation through company shares/RSUs. Annual bonus tied to performance. Hybrid work model (3 days in office, flexible remote days). Exclusive employee discounts. Clear path for career progression in a high-impact, data-first team. Annual performance reviews and merit-based More ❯

Calibrate confidence metrics with historical data and measure their value to trading & risk learning models. Continuously improve these models based on real-time data and feedback from trading activities. Model Communication: Explain uncertainty clearly, turning numbers into concise narratives and action-oriented alerts Broader Contributions: Build and refine statistical/ML models for short- to medium-term demand, renewables … output, and other fundamental time series. Help design feature pipelines, scenario tools and model-performance dashboards used daily by traders and analysts. Pitch in on ad-hoc analytics projects—anything from volatility clustering studies to optimisation of storage dispatch—whenever the desk needs statistical horsepower. REQUIREMENTS: Minimum of a degree in Statistics, Applied Maths, Physics or related field. Minimum More ❯

Calibrate confidence metrics with historical data and measure their value to trading & risk learning models. Continuously improve these models based on real-time data and feedback from trading activities. Model Communication: Explain uncertainty clearly, turning numbers into concise narratives and action-oriented alerts Broader Contributions: Build and refine statistical/ML models for short- to medium-term demand, renewables … output, and other fundamental time series. Help design feature pipelines, scenario tools and model-performance dashboards used daily by traders and analysts. Pitch in on ad-hoc analytics projects—anything from volatility clustering studies to optimisation of storage dispatch—whenever the desk needs statistical horsepower. REQUIREMENTS: Minimum of a degree in Statistics, Applied Maths, Physics or related field. Minimum More ❯

Calibrate confidence metrics with historical data and measure their value to trading & risk learning models. Continuously improve these models based on real-time data and feedback from trading activities. Model Communication: Explain uncertainty clearly, turning numbers into concise narratives and action-oriented alerts Broader Contributions: Build and refine statistical/ML models for short- to medium-term demand, renewables … output, and other fundamental time series. Help design feature pipelines, scenario tools and model-performance dashboards used daily by traders and analysts. Pitch in on ad-hoc analytics projects—anything from volatility clustering studies to optimisation of storage dispatch—whenever the desk needs statistical horsepower. REQUIREMENTS: Minimum of a degree in Statistics, Applied Maths, Physics or related field. Minimum More ❯

Calibrate confidence metrics with historical data and measure their value to trading & risk learning models. Continuously improve these models based on real-time data and feedback from trading activities. Model Communication: Explain uncertainty clearly, turning numbers into concise narratives and action-oriented alerts Broader Contributions: Build and refine statistical/ML models for short- to medium-term demand, renewables … output, and other fundamental time series. Help design feature pipelines, scenario tools and model-performance dashboards used daily by traders and analysts. Pitch in on ad-hoc analytics projects—anything from volatility clustering studies to optimisation of storage dispatch—whenever the desk needs statistical horsepower. REQUIREMENTS: Minimum of a degree in Statistics, Applied Maths, Physics or related field. Minimum More ❯

Calibrate confidence metrics with historical data and measure their value to trading & risk learning models. Continuously improve these models based on real-time data and feedback from trading activities. Model Communication: Explain uncertainty clearly, turning numbers into concise narratives and action-oriented alerts Broader Contributions: Build and refine statistical/ML models for short- to medium-term demand, renewables … output, and other fundamental time series. Help design feature pipelines, scenario tools and model-performance dashboards used daily by traders and analysts. Pitch in on ad-hoc analytics projects—anything from volatility clustering studies to optimisation of storage dispatch—whenever the desk needs statistical horsepower. REQUIREMENTS: Minimum of a degree in Statistics, Applied Maths, Physics or related field. Minimum More ❯

Calibrate confidence metrics with historical data and measure their value to trading & risk learning models. Continuously improve these models based on real-time data and feedback from trading activities. Model Communication: Explain uncertainty clearly, turning numbers into concise narratives and action-oriented alerts Broader Contributions: Build and refine statistical/ML models for short- to medium-term demand, renewables … output, and other fundamental time series. Help design feature pipelines, scenario tools and model-performance dashboards used daily by traders and analysts. Pitch in on ad-hoc analytics projects—anything from volatility clustering studies to optimisation of storage dispatch—whenever the desk needs statistical horsepower. REQUIREMENTS: Minimum of a degree in Statistics, Applied Maths, Physics or related field. Minimum More ❯

them into testable modelling hypotheses Prototype and validate growth-focused models, including churn and purchase propensity, audience segmentation, uplift modelling, and customer lifecycle scoring Support experimentation programs with actionable model outputs that enable targeted testing and measurable outcomes Build and deliver reusable data science products in collaboration with analytics and engineering Clearly communicate your approach and findings to both … technical and non-technical partners, building confidence in data-driven solutions Drive data literacy and model adoption across the business, enabling broader use of predictive insights Stay up to date with emerging tools, techniques, and technologies to continuously improve modelling practices and business impact Our data scientists also have dedicated time for self-directed exploration (approximately 10%), giving you More ❯

requirements Liaise with the Product and Underwriting teams to ensure that pricing changes are consistent with product coverage and regulatory requirements Support the retail team with pricing changes and model improvements Stay up-to-date with industry trends, competitor activities, and developments in travel insurance pricing Identify opportunities for process improvements and automation in the pricing workflow, leveraging tools More ❯

and refine your skills in Python (e.g., Pandas, NumPy) and SQL for data manipulation and analysis. Support the development of machine learning models and algorithms, assisting in testing and validation processes. Contribute to research efforts by exploring and applying the latest data science techniques. Collaborate with cross-functional teams to define and improve data collection and integration strategies. Assist More ❯

apply machine learning and statistical techniques to business problems. You'll contribute to the research and implementation of new approaches to address complex problems and perform data analysis and model validation. You'll have the opportunity to present results to a variety of internal stakeholders. You will apply these techniques and algorithms to create dunnhumby science solutions that can More ❯

input Proficiency in data, modelling, pricing and reporting tasks Speedy delivery and accuracy of data, models, pricing rates and reports Ensure work is reliable and free of errors Ensure model accuracy and robustness meet the business need for stability and sustainability Creativity and innovation: Quantity and quality of new developments - develop new analytical solutions using industry best practice and More ❯

SQL, Bash, and Git, with hands-on experience in tools like Jupyter notebooks, Pandas, PyTorch, and more. Experience with A/B testing and other experimentation methods to validate model performance and business impact. Experience with cloud platforms (AWS, Databricks, Snowflake), containerisation tools (Docker, Kubernetes), and CI/CD pipelines. Strong problem-solving skills, creativity, and attention to detail. More ❯

and healthcare applications. Lead the transition of machine learning research into viable prototypes and scalable production systems. Apply advanced techniques in natural language processing and machine learning to enhance model performance. Validate and test models to ensure readiness for real-world deployment. Build prototypes and take ownership from the design to the production of AI-powered products from client More ❯

apply machine learning and statistical technqiues to business problems. You'll contribute to the research and implementation of new approaches to address complex problems and perform data analysis and model validation. You'll have the opportunity to present results to a variety of internal stakeholders. You will apply these techniques and algorithms to create dunnhumby science solutions that can More ❯

About the Role: Grade Level (for internal use): 11 The Role Associate, Review & Validation Grade (relevant for internal applicants only) 11 Location Primary: London/New York Secondary: Chicago. Team The Review & Validation team has global responsibility for the review and validation of all S&P Global Ratings' methodologies, including models and criteria. S&P Global Ratings … the framework for all of our published credit ratings and analyses and, as such, represent our most significant intellectual property. The team comprises both credit analysts as well as model specialists with experience in Ratings and the Capital Markets more broadly. Impact Work in a dynamic environment in a team that has global, cross-sector responsibilities. Opportunity to work … in a collegial culture with good potential for professional development and career growth gaining exposure to varied asset classes and sectors. Team members typically specialize in either model validation or criteria validation/credit review but will have the opportunity to develop skills and experience across both disciplines. Personal initiative, independence, strong time management skills, and an More ❯

years. Headquartered in London with 36 offices worldwide, the Group has over 1,800 employees across Europe, Asia and America. The Quantitative Analyst will continuously be challenged around model risk management, model validation, pricing methodology and quantitative model development of various pricing and risk engines. Will gain exposure to various asset classes with a strong appreciation … for the complexities across the various commodity, FX and equity markets. Analyse and find meaningful patterns on large data sets. Responsibilities: Contribute to the Model Risk framework for both house and client positions. Enhancement of the risk management infrastructure through the transformation of data. Deliver improvements to market risk processes, models and methodologies; improving the modelling of market risk … VaR (Value at Risk) engines for all asset classes including structured products. Be able to validate Margining Methodologies and engines for all asset classes including exotic derivative products. Ongoing model development for valuation and risk measurement, carrying out reviews and calibration of model parameters to help ensure best practice is followed. Develop and implement tactical & strategic risk tools More ❯

derivatives business. It covers equity flow products, equity structured & hybrid products, quantitative index and strategies business. Overall purpose of the role Documentation, testing and improvements of an internal risk model, which is owned by The QA Equity & Hybrid Products team and feeds the Credit Valuation Adjustment (CVA) for products sensitive to future implied volatility dynamics (e.g. Corridor Variance Swaps … Liaise with Front Office, Technology and Model Validation teams, to deploy the risk model to production Candidate profile Masters or PhD in Mathematics/Computer Science or related field Mathematically minded (knowledge of financial mathematics, ability to program numerical algorithms in C++) Experience in Front Office & Derivatives modelling Theoretical knowledge of financial engineering/structuring and financial More ❯

a multi-agent system. Drive Deployment and ML Operations: Collaborate with DevOps to containerise and deploy monitors with automated testing and evaluation tools. Support ML Ops development to track model health, detect drift/skew, and ensure model reliability in production. Focus on Scalability and Clean Code: Write clear, well-documented, and reusable code in line with engineering … coding skills in Python and working knowledge of SQL and cloud platforms (preferably Azure). Experience with ML frameworks such as TensorFlow or PyTorch. Understanding of ML lifecycles, including model training, validation, testing, and deployment. Exposure to tools such as LangChain, OpenAI, Alembic, and orchestration with Poetry and Mypy is a plus. It’s A Bonus If You … machine learning or related fields. Interest in secure, scalable, and ethical AI systems. The Benefits: Join an innovation-driven team working on high-impact, future-ready tech. Hybrid working model with a central London base. Exposure to emerging AI tools and systems. Competitive compensation, performance bonus, and career growth opportunities. If you're a creative and driven Machine Learning More ❯

a multi-agent system. Drive Deployment and ML Operations: Collaborate with DevOps to containerise and deploy monitors with automated testing and evaluation tools. Support ML Ops development to track model health, detect drift/skew, and ensure model reliability in production. Focus on Scalability and Clean Code: Write clear, well-documented, and reusable code in line with engineering … coding skills in Python and working knowledge of SQL and cloud platforms (preferably Azure). Experience with ML frameworks such as TensorFlow or PyTorch. Understanding of ML lifecycles, including model training, validation, testing, and deployment. Exposure to tools such as LangChain, OpenAI, Alembic, and orchestration with Poetry and Mypy is a plus. It’s A Bonus If You … machine learning or related fields. Interest in secure, scalable, and ethical AI systems. The Benefits: Join an innovation-driven team working on high-impact, future-ready tech. Hybrid working model with a central London base. Exposure to emerging AI tools and systems. Competitive compensation, performance bonus, and career growth opportunities. If you're a creative and driven Machine Learning More ❯

a multi-agent system. Drive Deployment and ML Operations: Collaborate with DevOps to containerise and deploy monitors with automated testing and evaluation tools. Support ML Ops development to track model health, detect drift/skew, and ensure model reliability in production. Focus on Scalability and Clean Code: Write clear, well-documented, and reusable code in line with engineering … coding skills in Python and working knowledge of SQL and cloud platforms (preferably Azure). Experience with ML frameworks such as TensorFlow or PyTorch. Understanding of ML lifecycles, including model training, validation, testing, and deployment. Exposure to tools such as LangChain, OpenAI, Alembic, and orchestration with Poetry and Mypy is a plus. It’s A Bonus If You … machine learning or related fields. Interest in secure, scalable, and ethical AI systems. The Benefits: Join an innovation-driven team working on high-impact, future-ready tech. Hybrid working model with a central London base. Exposure to emerging AI tools and systems. Competitive compensation, performance bonus, and career growth opportunities. If you're a creative and driven Machine Learning More ❯

large media datasets from various sources for analysis. Statistical Analysis: Use econometric techniques like regression, time series, and panel data analysis to identify relationships between media spend and outcomes. Model Validation and Interpretation: Evaluate model accuracy, interpret results, and communicate findings clearly to stakeholders. Advanced Analytics: Explore machine learning techniques to improve models and uncover deeper insights. More ❯

a multi-agent system. Drive Deployment and ML Operations: Collaborate with DevOps to containerise and deploy monitors with automated testing and evaluation tools. Support ML Ops development to track model health, detect drift/skew, and ensure model reliability in production. Focus on Scalability and Clean Code: Write clear, well-documented, and reusable code in line with engineering … coding skills in Python and working knowledge of SQL and cloud platforms (preferably Azure). Experience with ML frameworks such as TensorFlow or PyTorch. Understanding of ML lifecycles, including model training, validation, testing, and deployment. Exposure to tools such as LangChain, OpenAI, Alembic, and orchestration with Poetry and Mypy is a plus. It’s A Bonus If You … machine learning or related fields. Interest in secure, scalable, and ethical AI systems. The Benefits: Join an innovation-driven team working on high-impact, future-ready tech. Hybrid working model with a central London base. Exposure to emerging AI tools and systems. Competitive compensation, performance bonus, and career growth opportunities. If you're a creative and driven Machine Learning More ❯

Senior Machine Learning Operation Engineers to join our Data Function. You'll play a significant role within our Data Function, working on the design and implementation of machine learning model engineering frameworks, solutions, and best practices. You'll be technically proficient in machine learning and its applications; you'll demonstrate an understanding of data management and show a keen … Engineering, Architecture, and Software Development to ensure efficient operation and use of Data Science models and will facilitate the full life cycle of machine learning models from data ingestion, model development, testing, validation, deployment, to monitoring and retraining of models within different environments. If you've a strong understanding of Microsoft Azure, fluency in data science coding, and … skills Powering the business with the right tools What's involved: You'll contribute to the design and implementation of Machine Learning Engineering standards and frameworks. You'll support model development, with an emphasis on auditability, versioning, and data security. You'll implement automated data science model testing and validation. You'll assist in the optimisation of deployed More ❯

Senior Machine Learning Operation Engineers to join our Data Function. You'll play a significant role within our Data Function, working on the design and implementation of machine learning model engineering frameworks, solutions, and best practices. You'll be technically proficient in machine learning and its applications; you'll demonstrate an understanding of data management and show a keen … Engineering, Architecture, and Software Development to ensure efficient operation and use of Data Science models and will facilitate the full life cycle of machine learning models from data ingestion, model development, testing, validation, deployment, to monitoring and retraining of models within different environments. If you've a strong understanding of Microsoft Azure, fluency in data science coding, and … skills Powering the business with the right tools What's involved: You'll contribute to the design and implementation of Machine Learning Engineering standards and frameworks. You'll support model development, with an emphasis on auditability, versioning, and data security. You'll implement automated data science model testing and validation. You'll assist in the optimisation of deployed More ❯