26 to 50 of 132 Model Validation Jobs in London

Head of Quantitative Risk Analytics – Quantitative Finance, Counterparty Credit Risk, Model Development, Model Validation, Risk Analysis, Python, R, SQL, Numerix, - City of London, Permanent A senior Quantitative Specialist is sought after by a Global Investment Bank to take ownership of their European Counterparty Credit Risk (CRR) modelling function, as part of the wider Risk Analytics group. In … this role, you will be responsible for managing the end-to-end modelling lifecycle, being responsible for methodology, model design and development, through to implementation and validation, helping support local Counterparty Credit Risk Management. This will be a multi-functional role, with responsibility for building and maintaining the modelling infrastructure and ecosystem, as well as undertaking quantitative research … to keep models up to date ensuring the business have access to accurate analytics. You will work closely with the business and other quantitative specialists for a cohesive model development process, including the implementation of highly accessible tools and dashboards for users to effectively undertake risk analysis. To be successful, you will demonstrate: Minimum of a Master’s degree More ❯

and strategy indices. Key Responsibilities Maintain and enhance internal risk models used in CVA calculations for volatility-sensitive products (e.g., Corridor Variance Swaps) Collaborate with Front Office, Technology, and Model Validation teams to deploy models Document, test, and validate model outputs Ensure model accuracy, robustness, and compliance Share best practices and support knowledge transfer across teams … mathematical and programming skills (C++, Python) Experience in derivatives modeling and front-office environments Knowledge of financial engineering and product structuring Strong analytical and communication skills High standards for model integrity and accuracy Desirable Self-motivated with attention to deadlines and quality Innovative mindset and proactive approach 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 ❯

in advanced analytics, quantitative finance, and technology advisory for leading institutions across capital markets. The firm partners with clients to design and implement high-impact solutions in electronic trading, model development, and risk management. Leveraging deep domain expertise and cutting-edge technologies, it delivers tailored strategies that enhance performance, reduce complexity, and support regulatory alignment across the financial services … join a specialized consulting team tasked with designing and delivering quantitative trading and risk solutions for clients in global interest rate markets. This role involves leading engagements focused on model development, system architecture, and algorithmic design for pricing and electronic trading. Through deep collaboration with client stakeholders, the consultant will drive impactful outcomes by applying quantitative rigor and engineering … Translate technical outputs into actionable insights for both technical and non-technical stakeholders. Support project scoping, planning, and prioritization in alignment with client objectives. Assist clients in enhancing their model governance frameworks through technical review and effective challenge. Advise on best practices in model development, validation, and documentation across trading and risk domains. Guide clients in aligning 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 ❯

models for the equity derivatives business, covering equity flow products, equity structured & hybrid products, quantitative index, and strategies business. Key Responsibilities: Documentation, testing, and improvements of an internal risk model owned by the QA Equity & Hybrid Products team, feeding the Credit Valuation Adjustment (CVA) for products sensitive to implied volatility dynamics (e.g., Corridor Variance Swaps). Liaise with Front … Office, Technology, and Model Validation teams to deploy the risk model to production. Key Skills & Experience: Master's or PhD in Mathematics, Computer Science, or related field preferred. Mathematically inclined with knowledge of financial mathematics and ability to program numerical algorithms in C++. Experience in Front Office & Derivatives modeling. Theoretical knowledge of financial engineering/structuring and More ❯

for the equity derivatives business. It covers equity flow products, equity structured & hybrid products, quantitative index and strategies business. Key Responsibilities: * Documentation, Testing and improvements of an internal risk model, which is owned by The QA Equity & Hybrid Products team and feeds the Credit Valuation Adjustment (CVA) for products sensitive to future implied volatility dynamics (e.g Corridor Variance Swaps … . * Liaise with Front Office, Technology and Model Validation teams, to deploy the risk model to production Key Skills & Experience: * Ideally possess a Masters or PhD in Mathematics/Computer Science or related field * Mathematically minded (knowledge of financial mathematic, ability to program numerical algorithms in C++): * Experience in Front Office & Derivatives modelling * Theoretical knowledge of financial More ❯

problems or opportunities. AI Strategy: Contribute to the organisation's AI strategy by identifying opportunities for leveraging AI technologies to drive innovation, improve business processes, and enhance decision-making. Model Development and Evaluation: Contribute to the development, deployment, and evaluation of AI models and to the deployment and evaluation of off the shelf AI models. Collaboration and Stakeholder Management … with organisational goals. Prototyping, developing, and deploying machine learning applications into production. Contributing to our machine learning enabled, business-facing applications. Contributing effective, high quality code to our codebase. Model validation and model testing of production models. Presenting findings to senior internal and external stakeholders in written reports and presentations. This role is for you if: Python … for API and Model development (Machine learning frameworks and tooling e.g. Sklearn) and (Deep learning frameworks such as Pytorch and Tensorflow). Understanding of machine learning techniques. Experience with data manipulation libraries (e.g. Pandas, Spark, SQL). Git for version control. Cloud experience (we use Azure/GCP/AWS). Skills we'd also like to hear about More ❯

positions, systems, models, data inputs and pricing sources to ensure completeness, accuracy and validity of prices and margins. With Market Risk, research various instruments and margining methodologies and risk model parameters. Analyse and provide recommendations to improve the processes and procedures for ensuring accurate, daily mark-to-market of customer and company positions. Contribute to testing, maintenance, and implementation … of new risk models and systems. Carry out periodic and ad-hoc risk analytics on clients, trading books, and products to inform risk-management decisions Participate in risk model validation reviews with other risk, back-office and front-office personnel or groups. Participate in new product/system reviews and represent the Risk Valuation group point of view. More ❯

Social Responsibility and Wellbeing. If you want to find out more about life at Paysafe, check out our careers page here. How we work: We follow a hybrid working model, spending an average of three days per week at our office located in Gresham Street next to St Paul's cathedral with easy access and transport links via St … emerging fraud trends. Conducting analysis of fraud and money-laundering trends and risk controls between Consumer, Merchant and Crypto areas. Collaborating with the Machine Learning team to drive a model-first culture, leveraging data-driven models to enhance risk detection and decision-making. Being the point of contact for cross-functional teams, including Product, Engineering, Sales and Finance, to … of antifraud solutions/risk systems/device fingerprinting and CRM/case management tools. Knowledge about cyberthreats (e.g., malware, ransomware, botnets, exploit rootkits). Knowledge of machine learning model validation, swap population review, deployment. Any of the below will be an advantage: Knowledge of cards, chargebacks, collections, schemes, prepaid products, gift cards, crypto market. High attention to More ❯

A high level of mathematical competence and proficiency in statistics A solid grasp of essentially all of the standard data science techniques, for example, supervised/unsupervised machine learning, model cross validation, Bayesian inference, time-series analysis, simple NLP, effective SQL database querying, or using/writing simple APIs for models. We regard the ability to develop new More ❯

or wastage risks. Build and iterate on AI-powered decision support tools to optimize inventory management and buying policies. Design and execute experiments (A/B tests) to validate model performance and drive improvements in stock ordering strategies. Collaborate with Category and In-Stock teams to evolve the Stock Ordering Tool using intelligent algorithms and real-time data. Analyze … as Mathematics, Statistics, Computer Science, Data Science, or Engineering. Benefits: Comprehensive medical and dental insurance. Equity participation through company shares/RSUs. Annual bonus tied to performance. Hybrid work model (3 days in office, flexible remote days). Exclusive employee discounts. Clear path for career progression in a high-impact, data-first team. Annual performance reviews and merit-based More ❯

or wastage risks. Build and iterate on AI-powered decision support tools to optimize inventory management and buying policies. Design and execute experiments (A/B tests) to validate model performance and drive improvements in stock ordering strategies. Collaborate with Category and In-Stock teams to evolve the Stock Ordering Tool using intelligent algorithms and real-time data. Analyze … as Mathematics, Statistics, Computer Science, Data Science, or Engineering. Benefits: Comprehensive medical and dental insurance. Equity participation through company shares/RSUs. Annual bonus tied to performance. Hybrid work model (3 days in office, flexible remote days). Exclusive employee discounts. Clear path for career progression in a high-impact, data-first team. Annual performance reviews and merit-based More ❯

Calibrate confidence metrics with historical data and measure their value to trading & risk learning models. Continuously improve these models based on real-time data and feedback from trading activities. Model Communication: Explain uncertainty clearly, turning numbers into concise narratives and action-oriented alerts Broader Contributions: Build and refine statistical/ML models for short- to medium-term demand, renewables … output, and other fundamental time series. Help design feature pipelines, scenario tools and model-performance dashboards used daily by traders and analysts. Pitch in on ad-hoc analytics projects—anything from volatility clustering studies to optimisation of storage dispatch—whenever the desk needs statistical horsepower. REQUIREMENTS: Minimum of a degree in Statistics, Applied Maths, Physics or related field. Minimum More ❯

Calibrate confidence metrics with historical data and measure their value to trading & risk learning models. Continuously improve these models based on real-time data and feedback from trading activities. Model Communication: Explain uncertainty clearly, turning numbers into concise narratives and action-oriented alerts Broader Contributions: Build and refine statistical/ML models for short- to medium-term demand, renewables … output, and other fundamental time series. Help design feature pipelines, scenario tools and model-performance dashboards used daily by traders and analysts. Pitch in on ad-hoc analytics projects—anything from volatility clustering studies to optimisation of storage dispatch—whenever the desk needs statistical horsepower. REQUIREMENTS: Minimum of a degree in Statistics, Applied Maths, Physics or related field. Minimum More ❯

Calibrate confidence metrics with historical data and measure their value to trading & risk learning models. Continuously improve these models based on real-time data and feedback from trading activities. Model Communication: Explain uncertainty clearly, turning numbers into concise narratives and action-oriented alerts Broader Contributions: Build and refine statistical/ML models for short- to medium-term demand, renewables … output, and other fundamental time series. Help design feature pipelines, scenario tools and model-performance dashboards used daily by traders and analysts. Pitch in on ad-hoc analytics projects—anything from volatility clustering studies to optimisation of storage dispatch—whenever the desk needs statistical horsepower. REQUIREMENTS: Minimum of a degree in Statistics, Applied Maths, Physics or related field. Minimum More ❯

apply machine learning and statistical techniques to business problems. You'll contribute to the research and implementation of new approaches to address complex problems and perform data analysis and model validation. You'll have the opportunity to present results to a variety of internal stakeholders. You will apply these techniques and algorithms to create dunnhumby science solutions that can More ❯

input Proficiency in data, modelling, pricing and reporting tasks Speedy delivery and accuracy of data, models, pricing rates and reports Ensure work is reliable and free of errors Ensure model accuracy and robustness meet the business need for stability and sustainability Creativity and innovation: Quantity and quality of new developments - develop new analytical solutions using industry best practice and More ❯

apply machine learning and statistical technqiues to business problems. You'll contribute to the research and implementation of new approaches to address complex problems and perform data analysis and model validation. You'll have the opportunity to present results to a variety of internal stakeholders. You will apply these techniques and algorithms to create dunnhumby science solutions that can More ❯

a multi-agent system. Drive Deployment and ML Operations: Collaborate with DevOps to containerise and deploy monitors with automated testing and evaluation tools. Support ML Ops development to track model health, detect drift/skew, and ensure model reliability in production. Focus on Scalability and Clean Code: Write clear, well-documented, and reusable code in line with engineering … coding skills in Python and working knowledge of SQL and cloud platforms (preferably Azure). Experience with ML frameworks such as TensorFlow or PyTorch. Understanding of ML lifecycles, including model training, validation, testing, and deployment. Exposure to tools such as LangChain, OpenAI, Alembic, and orchestration with Poetry and Mypy is a plus. It’s A Bonus If You … machine learning or related fields. Interest in secure, scalable, and ethical AI systems. The Benefits: Join an innovation-driven team working on high-impact, future-ready tech. Hybrid working model with a central London base. Exposure to emerging AI tools and systems. Competitive compensation, performance bonus, and career growth opportunities. If you're a creative and driven Machine Learning More ❯

a multi-agent system. Drive Deployment and ML Operations: Collaborate with DevOps to containerise and deploy monitors with automated testing and evaluation tools. Support ML Ops development to track model health, detect drift/skew, and ensure model reliability in production. Focus on Scalability and Clean Code: Write clear, well-documented, and reusable code in line with engineering … coding skills in Python and working knowledge of SQL and cloud platforms (preferably Azure). Experience with ML frameworks such as TensorFlow or PyTorch. Understanding of ML lifecycles, including model training, validation, testing, and deployment. Exposure to tools such as LangChain, OpenAI, Alembic, and orchestration with Poetry and Mypy is a plus. It’s A Bonus If You … machine learning or related fields. Interest in secure, scalable, and ethical AI systems. The Benefits: Join an innovation-driven team working on high-impact, future-ready tech. Hybrid working model with a central London base. Exposure to emerging AI tools and systems. Competitive compensation, performance bonus, and career growth opportunities. If you're a creative and driven Machine Learning More ❯

Data Scientist - Customer Lifetime Value Hybrid in London/Remote within the UK We're looking for a Data Scientist Our Customer Lifetime Value (CLtV) model is a highly developed and tailored model, which is central to our business strategy at iwoca. As a Data Scientist in our CLtV team, you will be developing this model so … to iwoca. This concept is central to our business, influencing decisions across every department. The CLtV team is a small and versatile group of people who manage the CLtV model from the R&D stage all the way to deploying model releases into production. We manage data pipelines that enable the business to use our predictions in their … business. The role Your role as a Data Scientist in the CLtV team will involve growing and demonstrating your skills in several key areas, including but not limited to: Model development: Explore and integrate innovative modelling methods into our training pipeline to enhance the predictive power and flexibility of our model. Take responsibility for the full lifecycle of the More ❯

can drive value. In terms of more technical activities, the build of a computational twin involves a bunch of tasks common to all data science work such as EDA, model building, and model evaluation. In terms of other activities you'll do in the role: You'll be a leader within a cross-functional delivery team, working closely … A high level of mathematical competence and proficiency in statistics A solid grasp of essentially all of the standard data science techniques, for example, supervised/unsupervised machine learning, model cross validation, Bayesian inference, time-series analysis, simple NLP, effective SQL database querying, or using/writing simple APIs for models. We regard the ability to develop new 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 ❯

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 ❯