1 to 25 of 122 Model Validation Jobs in London

Job Title: Pricing Model Validation Analyst Location: London Department: Model Validation/Quantitative Analytics Reporting to: Head of Model Validation Overview: An international investment bank is seeking a Pricing Model Validation professional to join its London-based Model Validation team. This role focuses on the independent review and validation … of pricing and risk models used across the firm’s trading and risk platforms. The function sits independently from Risk and works closely with Front Office Quants, IT, and Model Developers. Key Responsibilities: Perform independent validation of pricing models cross asset classes, with a focus on derivatives. Assess the conceptual soundness, implementation correctness, and ongoing performance of pricing … and valuation models. Rebuild models in Python or other quantitative libraries to benchmark performance and accuracy. Review model documentation, assumptions, numerical methods, calibration techniques, and risk sensitivities. Conduct quantitative testing including backtesting, stress testing, and scenario analysis. Liaise with model developers and Front Office quants to understand model design and propose improvements where necessary. Contribute to validation More ❯

Job Title: Pricing Model Validation Analyst Location: London Department: Model Validation/Quantitative Analytics Reporting to: Head of Model Validation Overview: An international investment bank is seeking a Pricing Model Validation professional to join its London-based Model Validation team. This role focuses on the independent review and validation … of pricing and risk models used across the firm’s trading and risk platforms. The function sits independently from Risk and works closely with Front Office Quants, IT, and Model Developers. Key Responsibilities: Perform independent validation of pricing models cross asset classes, with a focus on derivatives. Assess the conceptual soundness, implementation correctness, and ongoing performance of pricing … and valuation models. Rebuild models in Python or other quantitative libraries to benchmark performance and accuracy. Review model documentation, assumptions, numerical methods, calibration techniques, and risk sensitivities. Conduct quantitative testing including backtesting, stress testing, and scenario analysis. Liaise with model developers and Front Office quants to understand model design and propose improvements where necessary. Contribute to validation More ❯

Credit Risk Model Validation Manager Up to £80,000 Hybrid London The Company I am hiring a Model Validation Manager for a top fintech based in London who have multiple portfolios across both unsecured lending and secured lending. You will be working with experts across the industry to validate risk models across the business using AI … and Machine learning modelling. The Role As a Model Validation Manager , you will be: Validating Credit Risk models like IFRS9 (PD, EAD, and LGD) Using analytics skills to improve credit risk models and model review practices Validating wider risk models covering AI, machine learning, reporting, and operational risk models Working with senior leadership to present findings of … validation exercises. Using tools like SAS, SQL, R and Python daily. Your skills and experience To be successful as a Model Validation Manager , you will need: Strong experience with SQL and python Strong experience with validating credit risk models. Experience working in financial services Excellent communication skills Strong stakeholder management A numeric degree from a top university More ❯

confident leader in risk. Why You’ll Thrive Here Career growth with purpose : start as a Senior Credit Risk Manager, with a clear path to expanded oversight in prudential, model validation, and stress testing. Inclusive and collaborative environment : thrive in a culture that values diverse perspectives and nurtures leadership, confidence, and innovation. Work-life balance you can lean … lending and forward-flow agreements. Monitor portfolio performance, detect emerging risks early, and recommend effective actions. Ensure robust credit assessment—from scoring and affordability checks to decision governance. Lead validation, calibration, and testing of models amid changing economic conditions and regulatory expectations. Model Development & Validation Champion model governance as the second line of defence, ensuring all … critical models align with our risk framework. Work alongside data scientists and partners to validate, back-test, and maintain model performance. Maintain clarity and structure through comprehensive model documentation and governance practices. Risk Reporting & Governance Craft and present risk insights to senior leadership and the Board. Contribute to setting risk appetite and limits, and support audits and regulatory More ❯

confident leader in risk. Why You’ll Thrive Here Career growth with purpose : start as a Senior Credit Risk Manager, with a clear path to expanded oversight in prudential, model validation, and stress testing. Inclusive and collaborative environment : thrive in a culture that values diverse perspectives and nurtures leadership, confidence, and innovation. Work-life balance you can lean … lending and forward-flow agreements. Monitor portfolio performance, detect emerging risks early, and recommend effective actions. Ensure robust credit assessment—from scoring and affordability checks to decision governance. Lead validation, calibration, and testing of models amid changing economic conditions and regulatory expectations. Model Development & Validation Champion model governance as the second line of defence, ensuring all … critical models align with our risk framework. Work alongside data scientists and partners to validate, back-test, and maintain model performance. Maintain clarity and structure through comprehensive model documentation and governance practices. Risk Reporting & Governance Craft and present risk insights to senior leadership and the Board. Contribute to setting risk appetite and limits, and support audits and regulatory More ❯

lending decisions and risk management strategies. Key Responsibilities: Develop, implement, and maintain credit risk scorecards, applying advanced statistical and machine learning techniques. Utilize Python for data extraction, feature engineering, model development, validation, and ongoing monitoring. Collaborate with risk management, analytics, and IT teams to ensure model robustness, compliance with regulatory standards, and effective integration into production systems. … Ensure adherence to best practices in model governance, validation, and documentation. Communicate technical findings and model insights clearly and effectively to both technical and non-technical stakeholders. Candidate Profile: Demonstrable experience in credit risk modelling or scorecard development, preferably within the lending or financial services sectors. Advanced skills in Python programming, with experience handling large datasets and … applying statistical modelling techniques. Comprehensive understanding of credit risk concepts, scorecard methodology, and relevant regulatory frameworks. Experience in model validation, performance monitoring, and governance processes. Strong communication skills, with the ability to present complex analytical outcomes clearly and succinctly. Why Join? This position offers the opportunity to work within a progressive lending organisation that values data-driven decision More ❯

lending decisions and risk management strategies. Key Responsibilities: Develop, implement, and maintain credit risk scorecards, applying advanced statistical and machine learning techniques. Utilize Python for data extraction, feature engineering, model development, validation, and ongoing monitoring. Collaborate with risk management, analytics, and IT teams to ensure model robustness, compliance with regulatory standards, and effective integration into production systems. … Ensure adherence to best practices in model governance, validation, and documentation. Communicate technical findings and model insights clearly and effectively to both technical and non-technical stakeholders. Candidate Profile: Demonstrable experience in credit risk modelling or scorecard development, preferably within the lending or financial services sectors. Advanced skills in Python programming, with experience handling large datasets and … applying statistical modelling techniques. Comprehensive understanding of credit risk concepts, scorecard methodology, and relevant regulatory frameworks. Experience in model validation, performance monitoring, and governance processes. Strong communication skills, with the ability to present complex analytical outcomes clearly and succinctly. Why Join? This position offers the opportunity to work within a progressive lending organisation that values data-driven decision 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 ❯

and deploy innovative and highly scalable models for predictive learning - Research and implement novel machine learning and statistical approaches - Work closely with software engineering teams to drive real-time model implementations and new feature creations - Work closely with business owners and operations staff to optimize various business operations - Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation - Mentor other scientists and engineers in the use of ML techniques About the team The India Machine Learning team works closely with the business and engineering teams in building ML solutions that create an impact for Amazon's IN businesses. This is a great opportunity to leverage your machine learning More ❯

to drive sustainable growth. Your role in the Team's Success The Head of Quantitative Analysis will lead our firm's quantitative research and analytical capabilities, overseeing the development, validation, and enhancement of quantitative models and analytical frameworks across multiple asset classes. This senior leadership role combines deep technical expertise with strategic analytical insights to drive data-driven decision … all quantitative research activities Research & Development Drive the innovation and enhancement of proprietary analytical models, valuation frameworks, and risk assessment tools Oversee the research process from hypothesis generation to model validation and implementation Evaluate and prioritize analytical initiatives based on business impact, feasibility, and strategic fit Stay at the forefront of developments in quantitative finance, machine learning, and … statistical modelling Foster a culture of intellectual rigor, analytical excellence, and continuous improvement Model Development & Validation Ensure robust development and validation of quantitative models across all business functions Oversee the implementation of analytical frameworks for portfolio optimization, performance attribution, and risk assessment Guide the integration of new analytical tools and methodologies into existing workflows Maintain model More ❯

serve to drive sustainable growth. Your role in the Teams Success The Head of Quantitative Analysis will lead our firm's quantitative research and analytical capabilities, overseeing the development, validation, and enhancement of quantitative models and analytical frameworks across multiple asset classes. This senior leadership role combines deep technical expertise with strategic analytical insights to drive data-driven decision … all quantitative research activities Research & Development Drive the innovation and enhancement of proprietary analytical models, valuation frameworks, and risk assessment tools Oversee the research process from hypothesis generation to model validation and implementation Evaluate and prioritize analytical initiatives based on business impact, feasibility, and strategic fit Stay at the forefront of developments in quantitative finance, machine learning, and … statistical modelling Foster a culture of intellectual rigor, analytical excellence, and continuous improvement Model Development & Validation Ensure robust development and validation of quantitative models across all business functions Oversee the implementation of analytical frameworks for portfolio optimization, performance attribution, and risk assessment Guide the integration of new analytical tools and methodologies into existing workflows Maintain model More ❯

to drive sustainable growth. Your role in the Team's Success The Head of Quantitative Analysis will lead our firm's quantitative research and analytical capabilities, overseeing the development, validation, and enhancement of quantitative models and analytical frameworks across multiple asset classes. This senior leadership role combines deep technical expertise with strategic analytical insights to drive data-driven decision … all quantitative research activities Research & Development Drive the innovation and enhancement of proprietary analytical models, valuation frameworks, and risk assessment tools Oversee the research process from hypothesis generation to model validation and implementation Evaluate and prioritize analytical initiatives based on business impact, feasibility, and strategic fit Stay at the forefront of developments in quantitative finance, machine learning, and … statistical modelling Foster a culture of intellectual rigor, analytical excellence, and continuous improvement Model Development & Validation Ensure robust development and validation of quantitative models across all business functions Oversee the implementation of analytical frameworks for portfolio optimization, performance attribution, and risk assessment Guide the integration of new analytical tools and methodologies into existing workflows Maintain model More ❯

assist in productionizing your ML models. - Run A/B experiments, gather data, and perform statistical analysis. - Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving. - Research new and innovative machine learning approaches. Why you will love this opportunity: Amazon is investing heavily in building a world-class More ❯

time-series analysis, machine learning, and financial theory to develop accurate, commericalizable financial models. Collaborate closely with engineering, data science, product management, and commercial teams to maintain and enhance model features, data pipelines, and analytical tools. Ensure model validation, back-testing, and continuous performance assessment, prioritizing scalability, reliability, and integrity. Provide thought leadership and strategic guidance on More ❯

that attribute spot metrics and project future requirement, produce quantitative analytics on historical metrics data. • Build quantitative tools to explain and perform scenario analyses on various liquidity metrics. • Write model documents and execute model validation process in accordance with firm policy for quantitative models. • Collaborate with non-engineers to explain model behavior. QUALIFICATIONS • Bachelor's degree … Python, C++ or Java. • Developing financial pricing models in any asset class. • Maintaining a production code base and daily production processes. • Preparing and submitting technical documents to support the validation of mathematical models. • Working with techniques of optimization, statistical analysis, including parameter estimation. ABOUT GOLDMAN SACHS At Goldman Sachs, we commit our people, capital and ideas to help our More ❯

Services Team supports analytic and generative AI products for decisioning, analytics, and fraud and identity globally. As a Lead Data Scientist, you will use your coding expertise (Python, SAS), model risk management and Gen AI knowledge and experience, and analytic consulting skills to lead client and internal engagements for Experian's new global product launch and early client success … client base. Lead client analytic consulting engagements with financial services clients, including pre-sales and demos, training, and client success activities to maximize client value. Leverage Gen AI and model development tools to create and maintain new model document templates to help clients meet Model Risk Management regulatory requirements. Stay informed about regulatory changes, technological advancements, and … model risk management processes and controls to ensure the technology stack meets all compliance requirements. Research and integrate new data assets from different sources into Experian's ML and AI platform. Develop and assess analytic tools developed internally and externally. Gather feedback from internal and external clients to guide new product development, feature prioritisation, and product evolution of tools More ❯

large media datasets from various sources for analysis. Statistical Analysis: Use econometric techniques like regression, time series, and panel data analysis to explore relationships between media spend and outcomes. Model Validation and Interpretation: Evaluate model accuracy, interpret results, and communicate findings clearly to stakeholders. Campaign Optimization: Provide insights to improve media buying strategies, including channel allocation and … budget optimization. Advanced Analytics: Explore machine learning techniques to enhance insights and model accuracy. Your Experience and Skills Data Science: Proficiency in Python, R, SQL, including data manipulation, statistical modeling, and visualization. Econometrics: Experience with regression, panel data analysis, and time series forecasting. Media Industry Knowledge: Understanding of media landscape, ad formats, audience measurement, and KPIs. Communication Skills: Ability More ❯

What you will be doing Support end-to-end deployment of ML models (batch and real-time) from code validation through to production rollout under guidance from senior team members. Work with Data Science teams to facilitate smooth model handover and ensure deployment readiness aligned with implementation standards. Build and maintain CI/CD pipelines for model deployment, scoring, and operational monitoring. Debug and fix pipeline issues including data ingestion problems, model scoring failures, and deployment errors. Write comprehensive tests for ML pipelines (unit, integration, validation) and implement data quality checks and operational monitoring. Ensure deployed models meet audit, reconciliation, and governance requirements. Monitor production models for operational health, troubleshoot failures, and track data …/variable drift over time. Work with Platform Engineers within the team to create reusable MLOps templates and support Data Scientists in using them effectively. Support model migrations across data sources, tools, systems, and platforms. Participate in code reviews, knowledge sharing, and pod activities (standups, grooming, delivery check-ins). Learn from senior team members and contribute to continuous More ❯

strong engineering, and has opinions on building reliable, scalable systems. What you will be doing Drive the development of telematics features from mobile sensor data, including project design, modelling, validation, and deployment. Conduct deep dives into driving signals, develop hypotheses, and evaluate their predictive power for risk. Design technical solutions with clear trade-offs around performance, scalability, and maintainability. More ❯

in a fast-paced environment. Key Responsibilities Lead the design, development, and maintenance of credit risk and affordability models using bureau, open banking, and behavioural data Own the full model lifecycle from data sourcing and feature engineering to validation, deployment, and monitoring Design and run A/B and champion/challenger tests to improve performance across approval … junior analysts/data scientists as the team expands Collaborate with data engineering to deploy models into production Work closely with stakeholders to define goals, communicate findings, and translate model outputs into business value About You You are an analytical thinker with a passion for using data to drive credit decisioning. You bring hands-on experience building machine learning … models for consumer credit and understand the nuances of data preparation, feature selection, and model validation in high-stakes environments. 5–7 years of experience in a credit-related data science or decision science role Proficiency in Python and experience with libraries such as scikit-learn, XGBoost, or LightGBM Strong SQL skills for data extraction and transformation Experience More ❯

in a fast-paced environment. Key Responsibilities Lead the design, development, and maintenance of credit risk and affordability models using bureau, open banking, and behavioural data Own the full model lifecycle from data sourcing and feature engineering to validation, deployment, and monitoring Design and run A/B and champion/challenger tests to improve performance across approval … junior analysts/data scientists as the team expands Collaborate with data engineering to deploy models into production Work closely with stakeholders to define goals, communicate findings, and translate model outputs into business value About You You are an analytical thinker with a passion for using data to drive credit decisioning. You bring hands-on experience building machine learning … models for consumer credit and understand the nuances of data preparation, feature selection, and model validation in high-stakes environments. 5–7 years of experience in a credit-related data science or decision science role Proficiency in Python and experience with libraries such as scikit-learn, XGBoost, or LightGBM Strong SQL skills for data extraction and transformation Experience More ❯

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 ou will do Support research and discovery phase for new and existing products/models. The primary areas include … Identity and Data Solutions. Actively participate in the development and enhancement of our Identity Graph, utilizing statistical and machine learning techniques to improve accuracy. Drive the onboarding and validation of new data vendors, by establishing statistical methodologies and conducting comprehensive analysis to ensure new data partners meet our quality standards. Analyze large datasets to identify trends, patterns, and insights … ad hoc requests from internal teams and clients, performing analyses 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 ❯

statistical techniques to extract insights and support data-driven decision-making Work alongside data engineering in requirements for data pipelines and feature engineering Promote best practices in data science, model validation, documentation, and reproducibility Qualifications Experience Strong coding skills in Python, including libraries such as pandas, scikit-learn, TensorFlow, or PyTorch Expert in Python and ML frameworks (PyTorch … and ability to present complex ideas to non-technical stakeholders Experience with cloud platforms (AWS, GCP, Azure) and tools like Databricks, Snowflake, or BigQuery Desirable Skills Familiarity with MLOps, model monitoring, and production deployment Experience in a specific domain (e.g., marketing, operations, fraud, personalization, NLP) is a plus Hands-on experience with LLM stacks (e.g., Mistral, LangChain, Chroma, Hugging More ❯

both qualitatively and quantitatively to ensure they meet rigorous scientific standards. Contribute to building our overall loss modelling framework, ensuring robustness and adaptability across diverse client requirements and geographies Model documentation and presentations to engage with stakeholder and customers, all while representing the team at international conferences and industry events Requirements: MSc or PhD Degree in Computer Science, Artificial More ❯