1 to 25 of 81 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 ❯

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 ❯

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

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

valuation models, and established "street practices" used for security valuation and portfolio risk analysis is important. The ability to select and apply suitable pricing models, coupled with knowledge of model limitations and appropriate adjustments, is crucial in delivering accurate valuations. A discerning eye for assessing the reasonableness of model results is of great value. In this role, interactions … in a technical or quantitative field (e.g., Mathematics, Physics, Engineering, or Quantitative Finance); a PhD or equivalent experience is a plus. Experience in a front-office, financial engineering, or model validation role, with expertise in derivatives and structured products, including pricing, valuation, and risk management. Strong quantitative and analytical skills, with a deep understanding of market conventions, derivative More ❯

with a minimum of 50% travel into the London office a month. The principal requirement of the role is to carry out quantitative analysis of potential counterparty credit risk model changes proposed in the context of regulatory or business requirements. Investigations will normally include model assessment, backed up by statistical tests and impact analyses. Prototype implementation, documentation and … implement the risk methods in the risk systems, whilst assisting the technical teams responsible for the production environment. · Ensure the methods are adequately documented to support internal reviews and validation by internal auditors or regulators, by providing sufficient developmental evidence (i.e. materially studies, description of assumptions, bench marking against external methodologies and justification of methodological choices); take the lead … in ensuring the successful review by model validation teams. Our requirements To be successful in this role, the candidate should meet the following requirements: · A strong academic background, with at minimum a Masters in mathematics, physics or quantitative finance. · Proven experience in a quantitative finance environment - counterparty risk. · Good knowledge of derivatives, their risk drivers and pricing models. 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 ❯