1 to 25 of 83 Model Validation Jobs in London

Model Risk Management Senior Analyst - Independent Validation - ICAAP - Retail Banking Excellent opportunity opens for a skilled Model Risk Management professional with strong experience performing independent model validations opens within a growing international Bank's Model Risk Management team. This is a great chance to take ownership of the end-to-end model validation process and present outcomes to senior stakeholders. The Model Risk Management (MRM) team are responsible for the design and maintenance of the Bank's Model Risk Management policy and framework, ensuring comprehensive model governance and carrying out model validations and reviews across all the Banks models. The successful candidate will contribute to the independent development … and validation of IRB models and ensuring that efficient model risk management (governance, model inventory management, recommendations, and action plans, among other responsibilities) is being applied in line with the MRM principles outlined in SS1/23. Responsibilities Operates in line with the Bank's Risk Management Framework (including sub-frameworks) and relevant risk and compliance policies More ❯

Model Validator London- Hybrid £800- £900pd PAYE emagine is a high-end professional services consultancy and solutions firm Specialising in providing business and technology services to the financial services sector, we power progress, solve challenges and deliver real results through tailored high-end consulting services and solutions. We have created a culture of openness and integrity by building genuine … and equitable working environment with our consultants and colleagues which stems from our core values: Confident, Dedicated, Responsible, Genuine. Join a leading organization in the finance sector, focusing on model risk management under Basel 3.1 regulations. We are seeking a Model Validator with a strong foundation in regulatory compliance and validation processes, ideally suited for experienced Quant … Analysts who wish to transition from model development to validation. Your role will emphasize the review and assurance of governance frameworks and the accuracy of self-assessments. Main Responsibilities This role will focus on ensuring the integrity of model validation practices. Conduct independent reviews and validations of models created by quant teams. Ensure compliance with Basel regulations More ❯

An excellent opportunity to join a growing Markets & AI Modelling team working on trade surveillance model validation projects. You'll be responsible for validating in-house and third-party surveillance systems designed to detect market abuse, insider trading, and other conduct risks, ensuring compliance with key policy standards and regulatory frameworks. This role offers the chance to work … within a forward-looking AI-focused team, applying advanced analytics and model validation techniques to high-impact surveillance systems. Scroll down for a complete overview of what this job will require Are you the right candidate for this opportunity What you'll be doing Validate and review trade surveillance models (machine learning, statistical, NLP). Configure and dynamically … tune third-party systems for market data changes. Perform benchmarking, backtesting, and stress testing in Python. Assess model documentation, conceptual soundness, and explainability. Evaluate data quality, model governance, and regulatory compliance. Collaborate with AI Modelling, Compliance, and Risk teams to address findings. What we're looking for Proven experience in trade surveillance model development or validation 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 ❯

Senior Quant/Risk Professional - AI Model Validation, Python, Trade Surveillance sought by leading investment bank based in the city of London. **Inside IR35 -2/3 days a week on site** Summary This is an exciting opportunity for a highly motivated professional to join a dynamic team focused on validating trade surveillance models. The role involves ensuring … 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 surveillance teams to communicate findings and support remediation Produce clear and actionable reports summarising validation outcomes and risk ratings for senior stakeholders Support regulatory validation More ❯

Senior Quant/Risk Professional - AI Model Validation, Python, Trade Surveillance sought by leading investment bank based in the city of London. **Inside IR35 -2/3 days a week on site** Summary This is an exciting opportunity for a highly motivated professional to join a dynamic team focused on validating trade surveillance models. The role involves ensuring … 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 surveillance teams to communicate findings and support remediation Produce clear and actionable reports summarising validation outcomes and risk ratings for senior stakeholders Support regulatory validation More ❯

gather requirements, design data flows, and help implement pricing models, APIs and analytical capabilities that drive better underwriting decisions. Key Responsibilities: Define and document requirements for pricing system integrations, model deployment and API workflows. Translate pricing models (Excel/Python/R) into technical specifications for developers and data engineers. Collaborate with underwriters and actuaries to improve model governance, version control and reporting. Support UAT, model validation and release testing. Deliver insights and metrics around model performance, quote success and underwriting efficiency. Partner with insurers and MGAs to streamline pricing and underwriting processes through automation and data. Required Skills & Experience: 3+ years in a Business Analyst or Technical Analyst role within insurance, reinsurance or … InsurTech. Experience with pricing or rating systems, underwriting workflows or model integration projects. Strong understanding of insurance data structures, rating factors and model governance. Skilled in SQL and BI tools (Power BI, Tableau, Looker). Comfortable working with APIs, data pipelines and collaborating with developers. Excellent communication and stakeholder management skills. Desirable: Exposure to cloud environments (AWS, Azure More ❯

gather requirements, design data flows, and help implement pricing models, APIs and analytical capabilities that drive better underwriting decisions. Key Responsibilities: Define and document requirements for pricing system integrations, model deployment and API workflows. Translate pricing models (Excel/Python/R) into technical specifications for developers and data engineers. Collaborate with underwriters and actuaries to improve model governance, version control and reporting. Support UAT, model validation and release testing. Deliver insights and metrics around model performance, quote success and underwriting efficiency. Partner with insurers and MGAs to streamline pricing and underwriting processes through automation and data. Required Skills & Experience: 3+ years in a Business Analyst or Technical Analyst role within insurance, reinsurance or … InsurTech. Experience with pricing or rating systems, underwriting workflows or model integration projects. Strong understanding of insurance data structures, rating factors and model governance. Skilled in SQL and BI tools (Power BI, Tableau, Looker). Comfortable working with APIs, data pipelines and collaborating with developers. Excellent communication and stakeholder management skills. Desirable: Exposure to cloud environments (AWS, Azure More ❯

gather requirements, design data flows, and help implement pricing models, APIs and analytical capabilities that drive better underwriting decisions. Key Responsibilities: Define and document requirements for pricing system integrations, model deployment and API workflows. Translate pricing models (Excel/Python/R) into technical specifications for developers and data engineers. Collaborate with underwriters and actuaries to improve model governance, version control and reporting. Support UAT, model validation and release testing. Deliver insights and metrics around model performance, quote success and underwriting efficiency. Partner with insurers and MGAs to streamline pricing and underwriting processes through automation and data. Required Skills & Experience: 3+ years in a Business Analyst or Technical Analyst role within insurance, reinsurance or … InsurTech. Experience with pricing or rating systems, underwriting workflows or model integration projects. Strong understanding of insurance data structures, rating factors and model governance. Skilled in SQL and BI tools (Power BI, Tableau, Looker). Comfortable working with APIs, data pipelines and collaborating with developers. Excellent communication and stakeholder management skills. Desirable: Exposure to cloud environments (AWS, Azure More ❯

gather requirements, design data flows, and help implement pricing models, APIs and analytical capabilities that drive better underwriting decisions. Key Responsibilities: Define and document requirements for pricing system integrations, model deployment and API workflows. Translate pricing models (Excel/Python/R) into technical specifications for developers and data engineers. Collaborate with underwriters and actuaries to improve model governance, version control and reporting. Support UAT, model validation and release testing. Deliver insights and metrics around model performance, quote success and underwriting efficiency. Partner with insurers and MGAs to streamline pricing and underwriting processes through automation and data. Required Skills & Experience: 3+ years in a Business Analyst or Technical Analyst role within insurance, reinsurance or … InsurTech. Experience with pricing or rating systems, underwriting workflows or model integration projects. Strong understanding of insurance data structures, rating factors and model governance. Skilled in SQL and BI tools (Power BI, Tableau, Looker). Comfortable working with APIs, data pipelines and collaborating with developers. Excellent communication and stakeholder management skills. Desirable: Exposure to cloud environments (AWS, Azure More ❯

the project specification, incorporating all drivers of KPIs, providing rationale for variables selection, understanding coefficients and contributions. Taking base models, oversee or build in additional improvements and progress the model towards finalisation Create sales effect/ROI workbook, Create response curves and optimisation charts Budget allocation. Run scenarios required to answer client objectives for the purpose of forward looking More ❯

Robert Half Technology are assisting a market-leading financial services organisation to recruit a Quantitative Developer on a contract basis. This role offers a hybrid working model, based in London. Role Design, develop, and maintain quantitative libraries, models, and tools supporting trading, pricing, and risk management. Collaborate with quantitative analysts, data scientists, and traders to implement and optimise models … systems for data processing, pricing, and simulation. Translate complex mathematical models into robust, efficient, and maintainable code. Ensure system reliability, scalability, and low latency across all components. Participate in model validation, performance tuning, and version control processes. Stay up to date with advances in quantitative finance, computational techniques, and emerging technologies. Profile Strong programming experience in Python, C++ More ❯

scale machine learning systems that forecast demand, optimise staffing, and improve operational performance across thousands of venues. Lead projects end-to-end, from data design and modelling through to validation, deployment, and monitoring. Develop AI systems across areas such as computer vision, forecasting, optimisation, and emerging generative or agentic models. Partner with engineers to design scalable ML pipelines, APIs More ❯

scale machine learning systems that forecast demand, optimise staffing, and improve operational performance across thousands of venues. Lead projects end-to-end, from data design and modelling through to validation, deployment, and monitoring. Develop AI systems across areas such as computer vision, forecasting, optimisation, and emerging generative or agentic models. Partner with engineers to design scalable ML pipelines, APIs More ❯

role centers on evaluating analytical workflows, modeling standards, experimentation culture, and applied business impact . This position is ideal for someone with a strong background in applied data science, model lifecycle design, and organizational data maturity capable of analyzing current practices and defining what best-in-class looks like for scalable, responsible, and high-impact data science operations. Key … Responsibilities Practice Maturity Assessment: Evaluate current data science processes, tools, and team structures to determine capability strengths, weaknesses, and improvement areas. Framework Design: Develop and apply a structured maturity model to assess how data science work is conceived, executed, validated, and scaled. Model Lifecycle Review: Assess practices across data preparation, feature engineering, model development, validation, monitoring … . Collaboration & Alignment: Work with AI and Data & AI Architects to connect findings from people, platform, and practice assessments into a unified capability map. Gap Identification: Identify gaps in model governance, documentation, and model-to-business translation and recommend actionable improvement pathways. Reporting & Advisory: Produce detailed reports summarizing data science maturity, practice gaps, and recommendations for scaling responsibly More ❯

role centers on evaluating analytical workflows, modeling standards, experimentation culture, and applied business impact . This position is ideal for someone with a strong background in applied data science, model lifecycle design, and organizational data maturity capable of analyzing current practices and defining what best-in-class looks like for scalable, responsible, and high-impact data science operations. Key … Responsibilities Practice Maturity Assessment: Evaluate current data science processes, tools, and team structures to determine capability strengths, weaknesses, and improvement areas. Framework Design: Develop and apply a structured maturity model to assess how data science work is conceived, executed, validated, and scaled. Model Lifecycle Review: Assess practices across data preparation, feature engineering, model development, validation, monitoring … . Collaboration & Alignment: Work with AI and Data & AI Architects to connect findings from people, platform, and practice assessments into a unified capability map. Gap Identification: Identify gaps in model governance, documentation, and model-to-business translation and recommend actionable improvement pathways. Reporting & Advisory: Produce detailed reports summarizing data science maturity, practice gaps, and recommendations for scaling responsibly More ❯

role centers on evaluating analytical workflows, modeling standards, experimentation culture, and applied business impact . This position is ideal for someone with a strong background in applied data science, model lifecycle design, and organizational data maturity - capable of analyzing current practices and defining what "best-in-class" looks like for scalable, responsible, and high-impact data science operations. Key … Responsibilities • Practice Maturity Assessment: Evaluate current data science processes, tools, and team structures to determine capability strengths, weaknesses, and improvement areas. • Framework Design: Develop and apply a structured maturity model to assess how data science work is conceived, executed, validated, and scaled. • Model Lifecycle Review: Assess practices across data preparation, feature engineering, model development, validation, monitoring … . • Collaboration & Alignment: Work with AI and Data & AI Architects to connect findings from people, platform, and practice assessments into a unified capability map. • Gap Identification: Identify gaps in model governance, documentation, and model-to-business translation and recommend actionable improvement pathways. • Reporting & Advisory: Produce detailed reports summarizing data science maturity, practice gaps, and recommendations for scaling responsibly More ❯

role centers on evaluating analytical workflows, modeling standards, experimentation culture, and applied business impact . This position is ideal for someone with a strong background in applied data science, model lifecycle design, and organizational data maturity — capable of analyzing current practices and defining what “best-in-class” looks like for scalable, responsible, and high-impact data science operations. Key … Responsibilities • Practice Maturity Assessment: Evaluate current data science processes, tools, and team structures to determine capability strengths, weaknesses, and improvement areas. • Framework Design: Develop and apply a structured maturity model to assess how data science work is conceived, executed, validated, and scaled. • Model Lifecycle Review: Assess practices across data preparation, feature engineering, model development, validation, monitoring … . • Collaboration & Alignment: Work with AI and Data & AI Architects to connect findings from people, platform, and practice assessments into a unified capability map. • Gap Identification: Identify gaps in model governance, documentation, and model-to-business translation and recommend actionable improvement pathways. • Reporting & Advisory: Produce detailed reports summarizing data science maturity, practice gaps, and recommendations for scaling responsibly More ❯

role centers on evaluating analytical workflows, modeling standards, experimentation culture, and applied business impact . This position is ideal for someone with a strong background in applied data science, model lifecycle design, and organizational data maturity — capable of analyzing current practices and defining what “best-in-class” looks like for scalable, responsible, and high-impact data science operations. Key … Responsibilities • Practice Maturity Assessment: Evaluate current data science processes, tools, and team structures to determine capability strengths, weaknesses, and improvement areas. • Framework Design: Develop and apply a structured maturity model to assess how data science work is conceived, executed, validated, and scaled. • Model Lifecycle Review: Assess practices across data preparation, feature engineering, model development, validation, monitoring … . • Collaboration & Alignment: Work with AI and Data & AI Architects to connect findings from people, platform, and practice assessments into a unified capability map. • Gap Identification: Identify gaps in model governance, documentation, and model-to-business translation and recommend actionable improvement pathways. • Reporting & Advisory: Produce detailed reports summarizing data science maturity, practice gaps, and recommendations for scaling responsibly More ❯

role centers on evaluating analytical workflows, modeling standards, experimentation culture, and applied business impact . This position is ideal for someone with a strong background in applied data science, model lifecycle design, and organizational data maturity — capable of analyzing current practices and defining what “best-in-class” looks like for scalable, responsible, and high-impact data science operations. Key … Responsibilities • Practice Maturity Assessment: Evaluate current data science processes, tools, and team structures to determine capability strengths, weaknesses, and improvement areas. • Framework Design: Develop and apply a structured maturity model to assess how data science work is conceived, executed, validated, and scaled. • Model Lifecycle Review: Assess practices across data preparation, feature engineering, model development, validation, monitoring … . • Collaboration & Alignment: Work with AI and Data & AI Architects to connect findings from people, platform, and practice assessments into a unified capability map. • Gap Identification: Identify gaps in model governance, documentation, and model-to-business translation and recommend actionable improvement pathways. • Reporting & Advisory: Produce detailed reports summarizing data science maturity, practice gaps, and recommendations for scaling responsibly More ❯

role centers on evaluating analytical workflows, modeling standards, experimentation culture, and applied business impact . This position is ideal for someone with a strong background in applied data science, model lifecycle design, and organizational data maturity — capable of analyzing current practices and defining what “best-in-class” looks like for scalable, responsible, and high-impact data science operations. Key … Responsibilities • Practice Maturity Assessment: Evaluate current data science processes, tools, and team structures to determine capability strengths, weaknesses, and improvement areas. • Framework Design: Develop and apply a structured maturity model to assess how data science work is conceived, executed, validated, and scaled. • Model Lifecycle Review: Assess practices across data preparation, feature engineering, model development, validation, monitoring … . • Collaboration & Alignment: Work with AI and Data & AI Architects to connect findings from people, platform, and practice assessments into a unified capability map. • Gap Identification: Identify gaps in model governance, documentation, and model-to-business translation and recommend actionable improvement pathways. • Reporting & Advisory: Produce detailed reports summarizing data science maturity, practice gaps, and recommendations for scaling responsibly More ❯

role centers on evaluating analytical workflows, modeling standards, experimentation culture, and applied business impact . This position is ideal for someone with a strong background in applied data science, model lifecycle design, and organizational data maturity — capable of analyzing current practices and defining what “best-in-class” looks like for scalable, responsible, and high-impact data science operations. Key … Responsibilities • Practice Maturity Assessment: Evaluate current data science processes, tools, and team structures to determine capability strengths, weaknesses, and improvement areas. • Framework Design: Develop and apply a structured maturity model to assess how data science work is conceived, executed, validated, and scaled. • Model Lifecycle Review: Assess practices across data preparation, feature engineering, model development, validation, monitoring … . • Collaboration & Alignment: Work with AI and Data & AI Architects to connect findings from people, platform, and practice assessments into a unified capability map. • Gap Identification: Identify gaps in model governance, documentation, and model-to-business translation and recommend actionable improvement pathways. • Reporting & Advisory: Produce detailed reports summarizing data science maturity, practice gaps, and recommendations for scaling responsibly More ❯

Job Title: Data Scientist (Contract, Hybrid – London) Location: London (Hybrid: 2–3 days/week in office) Contract Type 6–12 months (Contract, possible extension) About The Role We are seeking a skilled Data Scientist to join our dynamic team More ❯

migration projects, ensuring data accuracy and completeness. Design, develop, and maintain dashboards and reports using Power BI (experience with Tableau is a plus). Perform data modeling, mapping, and validation to support business intelligence and reporting requirements. Communicate complex technical concepts effectively to both technical and non-technical stakeholders. Collaborate with cross-functional teams to identify opportunities for process More ❯