1 to 25 of 106 Permanent 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 ❯

Are you looking for a career move that will put you at the heart of a global financial institution? Then bring your skills and or experience in either model development or validation to Citi's Model Risk Management team that focus on validation of Equity & Hybrids derivative pricing models for Trading and Hedges. By Joining Citi … our clients by responsibly providing financial services that enable growth and economic progress. This position requires strong derivative pricing skills along with relevant industry experience.Validation work will involve reviewing model assumptions, verifying the mathematical formulation, independently implementing the business/desk model when needed, developing benchmark models to conduct effective challenge, and assessing and quantifying model limitations … to inform stakeholders of model risk to determine compensating controls. What you'll do? Manage model risk across the model lifecycle including model validation, ongoing performance evaluation and annual model reviews. Manage stakeholder interaction with model developers and business owners during the model lifecycle. Provide effective challenge to model assumptions, mathematical More ❯

modelling and analytics team within the CAT Risk function, reporting directly to the AVP for CAT Risk and Capital. Your role includes complex pricing support, portfolio analysis and optimisation, model validation, VoR, and other related areas. You should have a deep understanding of CAT models, hands-on experience validating and implementing new perils and regions. You will manage … Professional (CCRMP), or a CAT modelling designation from vendors like Verisk's CEEM. Technical skills required include proficiency in Microsoft Suite, SQL, geospatial tools, and statistical packages. Experience in model validation, leadership, change management, team development, and strategic alignment is essential. Strong organizational and communication skills are also required. Travelers Europe offers flexible hybrid work arrangements, allowing employees … to policy changes. What Will You Do? Provide complex pricing support to optimize risk assessment and pricing strategies. Conduct portfolio risk reward analysis to influence CAT underwriting strategy. Lead model validation efforts and participate in CAT View of Risk (VoR) discussions. Perform scenario testing and sensitivity analysis to refine catastrophe risk appetites and metrics. Maintain expertise in Data 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 ❯

key processes 2. Design, develop, evaluate and deploy, innovative and highly scalable ML/OR models 3. Work closely with other science and engineering teams to drive real-time model implementations 4. Work closely with Ops/Product partners to identify problems and propose machine learning solutions 5. Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model maintenance 6. Work proactively with engineering teams and product managers to evangelize new algorithms and drive the implementation of large-scale complex ML models in production 7. Leading projects and mentoring other scientists, engineers in the use of ML techniques BASIC QUALIFICATIONS - 5+ years of data scientist experience - Experience with data More ❯

and manage Ki's exposure to risk, effectively communicating this to the Board in alignment with our Risk Management Framework. You will also contribute to the delivery of internal model validation, ORSA, and other relevant requirements under Solvency II. You will develop and implement a comprehensive enterprise-wide ERM framework, calculate risk metrics, and assist in reporting breaches … also include contributing to the Own Risk and Solvency Assessment (ORSA), encompassing risk appetite setting, business plan reviews, and stress and scenario testing. You will assist in the internal model validation process and the production of validation reports, including independent evaluations of components of the internal model. Close collaboration with the Actuarial division is essential, and candidates More ❯

specific instances of risk or broader risk trends Design, development and evaluation of highly innovative models for risk management Working closely with software engineering teams to drive real-time model implementations and new feature creations Working closely with operations staff to optimize risk management operations, Establishing scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation Tracking general business activity and providing clear, compelling management reporting on a regular basis Research and implement novel machine learning and statistical approaches BASIC QUALIFICATIONS - Master's degree in computer science, mathematics, statistics, machine learning or equivalent quantitative field - Experience programming in Java, C++, Python or related language - Experience with SQL and an More ❯

of Visually Rich Documents and optimize key processes - Design, develop, evaluate and deploy, innovative and highly scalable ML models - Work closely with software engineering teams to drive real-time model implementations - Establish scalable, efficient, automated processes for large scale model development, model validation and model maintenance - Leading projects and mentoring other scientists, engineers in the 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 ❯

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 BASIC QUALIFICATIONS - Experience programming in Java, C++, Python or related language - Experience with SQL and an RDBMS (e.g., Oracle) or Data Warehouse PREFERRED QUALIFICATIONS - Experience implementing algorithms using both toolkits and self-developed code - Have publications at top-tier 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. - Recruit Applied Scientists to the team and provide mentorship. Why you will love this opportunity More ❯

significant project wins, the consultancy is seeking experienced credit risk professionals to lead delivery across a range of IRB retail portfolios. The roles offer a blend of hands-on model development and/or independent validation, combined with client advisory work in an evolving regulatory landscape. Candidates must bring: Extensive experience in IRB credit risk modelling or model validation within retail portfolios. Technical proficiency in Python, SAS, and SQL for data handling, analysis and model implementation. Strong working knowledge of PD, LGD or EAD methodologies. Experience managing workstreams and delivering directly to clients. An analytical mindset and structured approach to technical delivery and documentation. Responsibilities include: Leading the delivery of IRB model build or … validation projects for major clients. Engaging with client stakeholders to define scope, priorities and risks. Performing robust documentation and clearly communicating technical findings. Supporting and challenging assumptions to uphold best practice. Representing the consultancy with confidence and professionalism in client-facing roles. This position is ideally suited to technically capable individuals who enjoy hands-on delivery, thrive on intellectual 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 ❯

group’s cyber accumulation control framework for both affirmative and non-affirmative exposure. Building internal and external relationships to enhance existing processes and scenario usage. Supporting external third-party model validation work and understanding the vendor model ecosystem. Supporting the communication of Cyber View of Risk to key business stakeholders. Communicating model uncertainty (internal and external … model vendors), while still retaining credibility and confidence. Calculating PML figures for group company portfolios, as well as helping steer overall risk appetite for the group. Turning concepts and ideas into mathematical models for simulating losses against portfolio. Key Requirements Minimum of 3 years in a Cat Modelling/Exposure Management function. Expert is MS Excel. Skilled user of 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 ❯

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 ❯