1 to 25 of 40 Model Validation Jobs in Central London

every single requirement, please apply! You still may be a great fit for this role or other open roles. We are seeking candidates who model our values: invest in every relationship, lead with curiosity, champion diverse perspectives, turn inputs into actions, and uphold trust through integrity. Skills and Competencies … deep understanding of quantitative finance, modeling, and model validation, coupled with practical experience is required, along with a good understanding of financial products and markets. A deep understanding of AI model risk management, including risks and controls specific to Generative AI and Agentic AI, and their implications ...

liquidity risk associated with posted collateral. Our risk framework ensures resilience in dynamic market conditions while upholding the highest regulatory and operational standards. The Model Risk Management team, part of the Risk Oversight Department, is responsible for all aspects of model risk, encompassing model governance & control, model validation, and model performance monitoring across a wide range of applications. ICE Clear Europe is seeking a Senior Model Risk Analyst to join its Model Risk Management team. This role is responsible for validating and monitoring pricing and risk models used in the clearing house ...

Date Saturday 26 September 2026 Salary Range £122,009 - £143,540 Title: Senior Manager - Internal Model Method (IMM) Location: London HOURS: Full-time WORKING PATTERN: Our work style is hybrid, which involves spending at least two days per week, or 40% of our time, at one of our office … Front Office functions. Key responsibilities will include: Lead the development and enhancement of IMM methodologies for Counterparty Credit Risk. Deliver quantitative analysis supporting model approval and regulatory submissions. Engage with Model Validation, Audit and Regulatory stakeholders throughout the model lifecycle. Produce and maintain technical documentation, methodology ...

cases across Bloomberg, including product, platform, internal tooling, automation, and third-party AI solutions. Evaluate AI risks related to bias, explainability, hallucination, robustness, model drift, data leakage, privacy, security, intellectual property, misuse, transparency, and human oversight. Advise teams on appropriate controls, testing, monitoring, documentation, and risk mitigation strategies based … case, data sensitivity, model type, deployment context, and regulatory exposure. Review complex or higher-risk AI use cases and provide risk-based recommendations to governance forums and senior stakeholders. Help define practical technical standards for responsible AI development, testing, validation, deployment, monitoring, and retirement. Framework and Control Development ...

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 … 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 ...

fraud models are highly predictive and market leading - consumer bureau data, postcode insights, open source data,transactional insights & fraud indicators from partnerships Apply traditional model development techniques and approaches (e.g. logistic regression) as well as adopting new AI/ML techniques such as gradient boosting, random forests, clustering, etc. … approaches towards new fraud scores and models Consider the creation of new characteristics/attributes to improve and maximise the predictive power of the model(s) as well as enhancing and creating other analytical products and services. This can be done through expert approaches or through AI approaches (e.g. ...

Intelligence capability from driver‐based planning and package configuration towards ML‐driven forecasting. Owns the forecasting models from problem framing and data preparation through model validation, production integration, monitoring and adoption. The role works alongside the Planning & Performance Management practice and extends the range of propositions the practice … approaches rather than a single preferred method. Prepare and validate multi‐source data, engineer internal and external drivers, address seasonality and structural change, and model hierarchical relationships across products, entities, geographies or cost centres. Design rigorous back‐testing and time‐series cross‐validation, compare against transparent benchmarks ...

Digital Grid Solutions team in EMEA, being part of the Energy Control Systems (ECS) practice. This role focuses on data management, data integration, network model management and MDM (master data management). The customer base will primarily focus on transmission and distribution system operators, and occasionally on data centres … integration, DER/RES integration and corporate asset management. Responsibilities Develop and implement data governance practices, including data ownership, data quality controls, validation rules, metadata, versioning, and lifecycle management. Support data standardisation and harmonisation across network model datasets, systems, and stakeholders. Manage and maintain network model data ...

Intelligence capability from driver-based planning and package configuration towards ML-driven forecasting. Owns the forecasting models from problem framing and data preparation through model validation, production integration, monitoring and adoption. The role works alongside the Planning & Performance Management practice and extends the range of propositions the practice … approaches rather than a single preferred method. Prepare and validate multi-source data, engineer internal and external drivers, address seasonality and structural change, and model hierarchical relationships across products, entities, geographies or cost centres. Design rigorous back-testing and time-series cross-validation, compare against transparent benchmarks ...

Assurance/Validation Practice Leader AI Assurance/AI Validation Financial Services To 170k base + equity London An exceptional opportunity for a AI Assurance leader to join a global leader in AI Leading the AI Assurance and Validation capability across Financial Services you will build … lead the team, lead across GTM capability and drive revenue. Create value around model validation and 2nd line Defence. This is a unique career defining role where you will shape and develop the capability. Essential criteria You bring a strong technical background in model risk management, specifically ...

provide ongoing production support including incident triage and root-cause analysis. Own end-to-end delivery with Technology on implementation, testing and deployment. Drive model governance and continuous improvement in partnership with Model Validation, including documentation, controls, and ongoing performance monitoring. Required qualification, capabilities, and skills Advanced ...

Lorien in London is seeking an AI Assurance/Validation Practice Leader to head the AI Assurance and Validation capability within Financial Services. You will build and lead the team, shape GTM capability, and drive revenue while defining how model validation and second-line defence create … value for clients. The role requires a strong technical background in model risk management for AI/ML, a deep understanding of financial risks, and the ability to engage with auditors and regulators on global #J-18808-Ljbffr ...

models. Use data science techniques to support trading strategies and decision‐making. Build, test and validate models using historical and live data. Continuously assess model performance and identify areas for improvement. Present analytical findings clearly to both technical and non‐technical stakeholders. Contribute to the development of tools ...

grounded in trusted data and established metrics. About the role: We are seeking a Senior Data Scientist I to help with the design and validation of Agentic AI-driven product capabilities within Protégé in PatentSight. This role focuses on defining what to build and why, leveraging machine learning … including hybrid search (semantic + lexical), and evaluation metrics (e.g., relevance, ranking quality). Analyse large-scale IP datasets to extract insights and improve model performance. Establish best practices for model evaluation, validation, and benchmarking. Translate experimental results into clear product recommendations and business impact. Collaborate with ...

data validity Uncover trends in multiple sports datasets Build and maintain data-driven predictive models Research and apply novel modelling techniques Build and maintain model validation metrics to regularly track performance Have awareness of the limitations of any model output Have an understanding of statistical robustness ...

Bank of America in London is seeking a Quantitative Finance Analyst to join the Enterprise Model Risk Management team. You will validate risk models and work with developers to ensure robust monitoring and regulatory readiness. The role requires an advanced degree in a technical field and strong Python skills ...

ready insights grounded in trusted data and established metrics. About the role: We are seeking a Data Scientist III to help the design and validation of Agentic AI-driven product capabilities within Protégé in PatentSight. This role focuses on defining what to build and why, leveraging machine learning … including hybrid search (semantic + lexical), and evaluation metrics (e.g., relevance, ranking quality). Analyse large-scale IP datasets to extract insights and improve model performance. Establish best practices for model evaluation, validation, and benchmarking. Translate experimental results into clear product recommendations and business impact. Collaborate with ...

business. Work with exposure management team, claims and other areas of the business to collect data to help inform VoR improvements. Conduct selection and validation of new Catastrophe vendor models and products, incorporating them into Canopius VoR and processes. Develop research agenda that delivers commercial value to Canopius, working … Modeler experience is required Highly numerical and strong mathematical/statistical knowledge Excellent business communication skills - ability to influence, negotiate, and listen Experience in model validation and view of risk work is highly desirable. Ability to manipulate large data sets with strong Excel and SQL skills. Strong experience ...

solutions. Strong Salesforce administration, configuration, implementation and development experience. Experience delivering large-scale Experience Cloud implementations. Expertise in Salesforce customisation, security models, workflow approvals, validation rules and data management. Strong Apex development experience, including classes, controllers, triggers, Visualforce and web services. Experience developing Salesforce integrations using REST and SOAP ...

cross-asset workflows. What's the role? We are looking for a senior product manager to run IPQA's analytics architecture and drive model delivery at scale, ensuring our analytics continue to lead as client and market needs evolve. You will work at the intersection of quantitative finance, engineering … clients across Terminal, Enterprise Data and Enterprise Products. At the core of this role is a founding conviction: analytics at scale require a model-agnostic design, where the architecture enforces consistency and transparency across models, asset classes and client workflows. You will work closely with our quant and engineering ...

motivated Quantitative Analyst with a strong technical background and client-focused mindset. You will review and validate models used across asset classes, produce validation reports and contribute to the firm’s governance framework. The role involves developing risk models, building tools to enhance risk management processes, and presenting conclusions ...

encourage applications from people with diverse and underrepresented backgrounds and perspectives. Why you? Design and implement AI/ML-driven solutions throughout the entire model development life cycle. Research and develop state‐of‐the‐art machine learning models and agentic systems to solve a variety of scientific tasks. Deliver ...

business intelligence solutions, from requirements gathering through production deployment. Define and execute the AI and machine learning strategy, including use case prioritization, model lifecycle management, and Generative AI initiatives. Partner with Quantitative Research, Technology, and Product teams to develop, scale, and industrialize innovative AI and analytics capabilities. Drive … business-critical analytics solutions supporting deposits, liquidity exposure, balance sheet optimization, and revenue growth. Establish and maintain AI/ML governance frameworks, including documentation, validation, monitoring, bias reviews, and regulatory compliance requirements. Partner with Technology, Quantitative Research, and data platform teams to ensure adherence to analytics governance and firmwide ...

deliver BIM standards and a digital strategy across pre-contract and project delivery phases. The role requires technical leadership to implement BIM processes, model validation and 4D planning, with a focus on collaboration and continuous improvement. You will work with EIR/BEP reviews, 3D model federation ...

healthcare applications. The role sits at the intersection of clinical practice, software engineering, data science, and AI , with a strong focus on patient safety, model reliability, regulatory compliance, and real-world clinical impact. The successful candidate will work closely with clinicians, data scientists, ML engineers, software engineers, product teams … deep-learning models using appropriate clinical datasets. Develop robust data pipelines for clinical, imaging, laboratory, physiological, and/or electronic health-record data. Implement model evaluation frameworks covering performance, calibration, robustness, bias, uncertainty, and clinically relevant endpoints. Support prospective and retrospective validation of AI systems in clinical environments. ...