1 to 25 of 53 Permanent Model Validation Jobs in the UK

experiments to test new agent capabilities, fine-tune models, and iterate on prompt engineering and feature selection. • Automate data pipelines end-to-end, from data ingestion and preparation to model training, evaluation, and deployment, including integrating agents into cloud-native environments and ensuring they scale and operate reliably. • Engage confidently with both technical and non-technical stakeholders, adapting your … workflows. • Establish both generic and bespoke metrics for agent performance, using a mix of human and AI-based evaluation methods to ensure robust, scalable measurement. • Set up monitoring and validation frameworks to ensure agents perform as expected in production and quickly identify and address issues. • Work closely with engineering, DevOps, risk, security, and business teams to deliver agent-based … to innovate, explore possibilities and grow with purpose. What you'll need: • Experience working with AI agent including prompt engineering and tool definition/selection to build Large Language Model (LLM)-based applications. • Degree qualified in a relevant field or equivalent work experience. • Experience in leading a small team and managing projects. • Have industry experience as a data scientist More ❯

Responsibilities: Engage in the validation and approval sign off of the firm's models across Liquidity Risk, Market Risk, and Counterparty Risk models. Challenge model assumptions, implementations, and mathematical formulations. Review and oversee the monitoring of the performance of models including outcomes, verification, and benchmarking. Understand and communicate the risks of model limitations to senior management. Requirements … Education: PhD/Masters in a finance/mathematical/quantitative field Prior Experience: 3-5 years in model validation of liquidity/market/counterparty risk models. Knowledge: Strong understanding and experience working with ILST/VaR models Technical: Python More ❯

Responsibilities: Engage in the validation and approval sign off of the firm's models across Liquidity Risk, Market Risk, and Counterparty Risk models. Challenge model assumptions, implementations, and mathematical formulations. Review and oversee the monitoring of the performance of models including outcomes, verification, and benchmarking. Understand and communicate the risks of model limitations to senior management. Requirements … Education: PhD/Masters in a finance/mathematical/quantitative field Prior Experience: 3-5 years in model validation of liquidity/market/counterparty risk models. Knowledge: Strong understanding and experience working with ILST/VaR models Technical: Python More ❯

Responsibilities: Engage in the validation and approval sign off of the firm's models across Liquidity Risk, Market Risk, and Counterparty Risk models. Challenge model assumptions, implementations, and mathematical formulations. Review and oversee the monitoring of the performance of models including outcomes, verification, and benchmarking. Understand and communicate the risks of model limitations to senior management. Requirements … Education: PhD/Masters in a finance/mathematical/quantitative field Prior Experience: 3-5 years in model validation of liquidity/market/counterparty risk models. Knowledge: Strong understanding and experience working with ILST/VaR models Technical: Python More ❯

Responsibilities: Engage in the validation and approval sign off of the firm's models across Liquidity Risk, Market Risk, and Counterparty Risk models. Challenge model assumptions, implementations, and mathematical formulations. Review and oversee the monitoring of the performance of models including outcomes, verification, and benchmarking. Understand and communicate the risks of model limitations to senior management. Requirements … Education: PhD/Masters in a finance/mathematical/quantitative field Prior Experience: 3-5 years in model validation of liquidity/market/counterparty risk models. Knowledge: Strong understanding and experience working with ILST/VaR models Technical: Python More ❯

Responsibilities: Engage in the validation and approval sign off of the firm's models across Liquidity Risk, Market Risk, and Counterparty Risk models. Challenge model assumptions, implementations, and mathematical formulations. Review and oversee the monitoring of the performance of models including outcomes, verification, and benchmarking. Understand and communicate the risks of model limitations to senior management. Requirements … Education: PhD/Masters in a finance/mathematical/quantitative field Prior Experience: 3-5 years in model validation of liquidity/market/counterparty risk models. Knowledge: Strong understanding and experience working with ILST/VaR models Technical: Python More ❯

I am currently supporting a FinTech lender in London a new role within their Model Validation team. The role is at a Lead Analyst level and is an individual contributor position, there is no line management. The main responsibility within the role will be validating credit risk scorecards and there will also be validation of IFRS9 models. … You must have experience within a Model Validaiton function previously and any added experience of working within Model Development would be desirable (but not essential). The main coding language used is Python, but if you have experience in SAS or R with the desire to up skill in Python, this works for the business. InterQuest Group is More ❯

and Analytics teams and collaborate with product and engineering teams to work on Media Measurement and Data Solutions products. This includes data analysis, design of statistical and machine learning model methodologies and codebases, and model validation. The ideal candidate is a self-starter comfortable working with large datasets and knowledgeable in statistical and machine learning techniques, with an … eagerness to learn and contribute to the development and validation of products that align Cint capabilities with the market. What you will do Contribute to discovery and development phases for new and existing products/models relating to media measurement Participate in model development, validation and maintenance Analyze large datasets to identify trends, patterns, and insights, ensuring … ad hoc client-specific requests including performing analyses, data manipulation and producing summary results. Collaborate with cross-functional teams to deliver on broader project goals. Participate in developing methodologies, model validation, and maintenance and enhancement of existing statistical and machine learning models. Support evaluation and validation of both internal and external products to ensure Cint’s success. More ❯

and Analytics teams and collaborate with product and engineering teams to work on Media Measurement and Data Solutions products. This includes data analysis, design of statistical and machine learning model methodologies and codebases, and model validation. The ideal candidate is a self-starter comfortable working with large datasets and knowledgeable in statistical and machine learning techniques, with an … eagerness to learn and contribute to the development and validation of products that align Cint capabilities with the market. What you will do Contribute to discovery and development phases for new and existing products/models relating to media measurement Participate in model development, validation and maintenance Analyze large datasets to identify trends, patterns, and insights, ensuring … ad hoc client-specific requests including performing analyses, data manipulation and producing summary results. Collaborate with cross-functional teams to deliver on broader project goals. Participate in developing methodologies, model validation, and maintenance and enhancement of existing statistical and machine learning models. Support evaluation and validation of both internal and external products to ensure Cint’s success. More ❯

and Analytics teams and collaborate with product and engineering teams to work on Media Measurement and Data Solutions products. This includes data analysis, design of statistical and machine learning model methodologies and codebases, and model validation. The ideal candidate is a self-starter comfortable working with large datasets and knowledgeable in statistical and machine learning techniques, with an … eagerness to learn and contribute to the development and validation of products that align Cint capabilities with the market. What you will do Contribute to discovery and development phases for new and existing products/models relating to media measurement Participate in model development, validation and maintenance Analyze large datasets to identify trends, patterns, and insights, ensuring … ad hoc client-specific requests including performing analyses, data manipulation and producing summary results. Collaborate with cross-functional teams to deliver on broader project goals. Participate in developing methodologies, model validation, and maintenance and enhancement of existing statistical and machine learning models. Support evaluation and validation of both internal and external products to ensure Cint’s success. More ❯

the capital modelling process for each of the syndicates managed by PMA. This includes capital requirements calculated under syndicate internal models, Solvency II Standard Formula and Lloyd's Standard Model (where applicable). Provide robust challenge of capital methodology, assumptions and results where reliance is placed on PMA's clients or other external resources. Manage the deliverables from and … boarding of new syndicates/clients, supporting PMA's business development activities, and supporting new entrants through the Lloyd's application and Making It Happen processes. Oversee new internal model builds and IMAP applications and major Model Change applications for PMA clients as required. Monitoring, challenge, and-where necessary- improve the quality and flow of data used in … the internal model. Liaise with the risk management team and internal model validators to ensure model validation process is well supported, and to remediate and close validation issues. Liaise with the external stakeholders responsible for the management of each syndicate (PMA's clients) to gain understanding of business developments and to set and challenge key assumptions. More ❯

learning, statistical, optimisation and econometric methods 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 also have the opportunity to present results to both internal teams and clients. What you'll be working on Developing innovative methods to exploit dunnhumby's … world class Price & Promotions capabilities Supporting our high-performing Price & Promotions experts by implementing new capabilities with significant business impact Performing exploratory data analysis and model validation What we expect from you Master's degree/PhD in Computer Science, Machine Learning, Applied Statistics, Physics, Engineering or related field Strong mathematical and statistical skills Experience with Python. Spark More ❯

clearing, and collateral management for equities, fixed income and repo products. About the Role You will be part of a collaborative team focused on first-line risk management and model governance for trade, collateral, and liquidity oversight. Working closely with risk, business, and quant leads, you'll gain hands-on exposure across multiple asset classes while growing your technical … and stakeholder-facing skills. Key Responsibilities Drafting risk governance reports, model amendments and technical documentation for internal committees and senior stakeholders Supporting risk model reviews and scenario testing across repos, equities, and collateral portfolios Collaborating with quants, risk managers, and business partners to improve models, controls, and processes Presenting technical materials to risk committees and management, translating quant … risk controls, and product innovation Supporting continuous improvement in risk and control frameworks and day-to-day business decision-making Candidate Profile 3-7 years' experience in risk analytics, model validation, or quant analysis within financial markets, clearing, post-trade, or banking (middle office, treasury, or product control) Degree (ideally MSc/PhD) in a quantitative subject: Mathematics More ❯

pipelines, and ethical product delivery. Key Responsibilities Collaborate with product teams to identify opportunities for ML and data science integration Build and maintain data pipelines to support experimentation and model development Develop and deploy machine learning models in production environments Present insights and results to technical and non-technical stakeholders Apply statistical methods and model validation techniques … user-centric data products Stay curious, research new methods, and continually build your technical capability What We’re Looking For Proficiency in Python or similar languages for scripting and model building Hands-on experience with machine learning, model deployment, and performance evaluation Strong communication skills – able to simplify complex ideas for various audiences Awareness of Agile methodologies and More ❯

pipelines, and ethical product delivery. Key Responsibilities Collaborate with product teams to identify opportunities for ML and data science integration Build and maintain data pipelines to support experimentation and model development Develop and deploy machine learning models in production environments Present insights and results to technical and non-technical stakeholders Apply statistical methods and model validation techniques … user-centric data products Stay curious, research new methods, and continually build your technical capability What We’re Looking For Proficiency in Python or similar languages for scripting and model building Hands-on experience with machine learning, model deployment, and performance evaluation Strong communication skills – able to simplify complex ideas for various audiences Awareness of Agile methodologies and More ❯

pipelines, and ethical product delivery. Key Responsibilities Collaborate with product teams to identify opportunities for ML and data science integration Build and maintain data pipelines to support experimentation and model development Develop and deploy machine learning models in production environments Present insights and results to technical and non-technical stakeholders Apply statistical methods and model validation techniques … user-centric data products Stay curious, research new methods, and continually build your technical capability What We’re Looking For Proficiency in Python or similar languages for scripting and model building Hands-on experience with machine learning, model deployment, and performance evaluation Strong communication skills – able to simplify complex ideas for various audiences Awareness of Agile methodologies and More ❯

pipelines, and ethical product delivery. Key Responsibilities Collaborate with product teams to identify opportunities for ML and data science integration Build and maintain data pipelines to support experimentation and model development Develop and deploy machine learning models in production environments Present insights and results to technical and non-technical stakeholders Apply statistical methods and model validation techniques … user-centric data products Stay curious, research new methods, and continually build your technical capability What We’re Looking For Proficiency in Python or similar languages for scripting and model building Hands-on experience with machine learning, model deployment, and performance evaluation Strong communication skills – able to simplify complex ideas for various audiences Awareness of Agile methodologies and More ❯

pipelines, and ethical product delivery. Key Responsibilities Collaborate with product teams to identify opportunities for ML and data science integration Build and maintain data pipelines to support experimentation and model development Develop and deploy machine learning models in production environments Present insights and results to technical and non-technical stakeholders Apply statistical methods and model validation techniques … user-centric data products Stay curious, research new methods, and continually build your technical capability What We’re Looking For Proficiency in Python or similar languages for scripting and model building Hands-on experience with machine learning, model deployment, and performance evaluation Strong communication skills – able to simplify complex ideas for various audiences Awareness of Agile methodologies and More ❯

servers, audience panels) for analysis. Statistical Analysis: Utilise econometric techniques like regression analysis, time series modelling, and panel data analysis to identify relationships between media spend and business outcomes. Model Validation and Interpretation: Evaluate the accuracy and robustness of models, interpret results, and communicate findings to stakeholders in a clear and concise manner. Campaign Optimisation: Provide data-driven … insights to inform media buying strategies, including channel allocation, budget optimisation, and creative testing. Advanced Analytics: Explore new data analysis techniques like machine learning to enhance model accuracy and uncover deeper insights. Your Experience and Skills: Data Science: Proficient in programming languages like Python, R, and SQL including data manipulation, data imputation, statistical modelling, and visualisation libraries. Econometrics Background More ❯

What you'll be doing: Exploring, processing, and analysing complex time-series datasets. Designing and implementing advanced statistical, ML, and deep learning models for forecasting. Applying best practices in model development, testing, and validation. Working closely with quants and engineering teams to integrate models into investment workflows. Contributing directly to investment strategies with your research and insights. What we More ❯

and optimisation framework, conducting reviews of client's processes and procedures, support regulatory or audit reviews, advising on TM technology, optimisation, and remediation programmes Define and lead on TM model optimisation, industry monitoring typology risk assessment methodology and overall control framework in building an effective Transaction Monitoring programme Leading and developing strong relationships with project stakeholders Supporting with planning … defining change governance, project management and business analyst background. Must demonstrate strong capability to define and articulate approach Technical Skills: (Must have) Hands-on experience in defining and leading model validation and system tuning from inception to completion Hands-on understanding on minimum of one TM systems across rule designs, segment designs, technical design and processes (e.g NICE More ❯

inform business strategies. Statistical Modeling : The ability to applying statistical techniques to extract insights, build predictive models, interpret data, and support data driven decision making. Machine Learning and AI Model End to End Management : The ability to build and manage the full lifecycle of ML models including development, validation, deployment, and monitoring in production environments. Collaboration : The ability … develop, test, and deploy advanced machine learning models, ensuring alignment with business objectives and seamless integration into client operations. Communication : The skill to effectively communicate complex analytical findings and model results to stakeholders, translating data-driven insights into business language that informs decision-making. Continuous Learning : The ability to stay informed of the latest advancements in data science, including … AI principles and programming is essential for success in this role. Ideally, you will also have Problem-Solving: Ability to translate business assumptions and rules into feature engineering and model explainability, addressing business problems with data-driven solutions. Collaborative Development: Work under the guidance of senior data scientists and solution architects to build models that align with strategic visions More ❯

as a governance and architecture lead across multi-party AI initiatives. 4. Risk, Compliance & Responsible AI Ensure solutions are aligned with regulatory and compliance requirements (e.g., FINRA, SEC, GDPR, Model Risk Governance). Design solutions with embedded safeguards around transparency, explainability, auditability, and ethical AI usage. 5. Knowledge Development & Enablement Create reusable playbooks, frameworks, and GenAI solution kits specific … in both business and technology. Experience working in or with regulated financial environments and navigating security and compliance requirements. Preferred Qualifications Experience with retrieval augmented generation (RAG), fine-tuning, model evaluation, or deploying models in production environments. Understanding of financial risk modeling, model validation, or operational risk frameworks. Knowledge of regulatory frameworks such as DORA, SR More ❯

as a governance and architecture lead across multi-party AI initiatives. 4. Risk, Compliance & Responsible AI Ensure solutions are aligned with regulatory and compliance requirements (e.g., FINRA, SEC, GDPR, Model Risk Governance). Design solutions with embedded safeguards around transparency, explainability, auditability, and ethical AI usage. 5. Knowledge Development & Enablement Create reusable playbooks, frameworks, and GenAI solution kits specific … in both business and technology. Experience working in or with regulated financial environments and navigating security and compliance requirements. Preferred Qualifications Experience with retrieval augmented generation (RAG), fine-tuning, model evaluation, or deploying models in production environments. Understanding of financial risk modeling, model validation, or operational risk frameworks. Knowledge of regulatory frameworks such as DORA, SR More ❯

machine learning algorithms, including their strengths and weaknesses across different data types. Desire to see a data-driven project through all the way from initial research and experimentation, through model validation, to the delivery of actionable insights and automated processes. Demonstrated ability to present complex analytical findings clearly and concisely, and actively solicit and incorporate feedback. Proven ability More ❯