1 to 25 of 77 Model Validation Jobs in the UK

hackajob is collaborating with Vanguard to connect them with exceptional professionals for this role. Overview The Head of Validation, Model Risk is a senior leadership role responsible for setting enterprise direction for model validation delivering independent, risk-based oversight across a diverse portfolio of models spanning … management, fraud and compliance, finance and HR, and rapidly evolving Gen AI and agentic use cases. This role serves as the senior authority for model validation, setting the bar for defensible methodologies, rigorous challenge, and clear, decision-ready risk communication to senior leaders. The Head of Validation ...

Business Services, Corporate banking, Wealth Management, Group Functions, Retail and Investment Banking. On behalf of this organisation, AMS are looking for a Programme Lead (Model Validation Transformation) for a 6 Months (with likely extension) contract based in London or Edinburgh (Hybrid). Purpose of the role: As Programme … Lead with experience in Model Validation Transformation you will drive a high-profile transformation initiative within a Group Model Validation function. Operating at the intersection of risk, regulation, technology and AI, you will play a key role in shaping the future operating model, improving validation ...

# ML Model Governance LeadFinancial Services — Model Risk ManagementHybrid · London £95,000–£130,000 42 days ago 13 interestedModel Risk ManagementMLOpsModel ValidationSR 11-7Python## Job DescriptionThe ML Model Governance Lead owns the framework, processes and tooling that ensure machine learning models deployed in production are accurate … fair, compliant and monitored — a role that is rapidly becoming mandatory in regulated industries and is emerging in all large enterprises as AI model risk becomes a board-level concern.In financial services, the SR 11-7 guidance has defined model risk management for decades. In 2026, that framework ...

level risk. We are seeking an experienced Credit Risk Modeller with strong hands-on expertise in scorecard development, bureau data modelling, and regulatory-aligned model design. This is a key delivery role responsible for developing high-quality models that meet governance standards and are ready for deployment into … credit decisioning platform. This is a hands-on contractor opportunity, ideal for someone who can quickly integrate into the team, take ownership of model development, and deliver high-quality outputs at pace. Key Responsibilities Develop new credit risk models, including: Application scorecards Behavioural (in-life) scorecards Probability of Default ...

With Product, Commercial, and Clinical, choose what to build next, weighing clinical value, data, regulatory burden, and commercial pull. With QARA and Clinical, lead validation to prove each model meets its intended use, then work with engineering to get it production-ready. Monitor and maintain - Own model … demonstrable experience building clinical AI within a regulated medical device context. Your playground is pre-/silent/post- deployments, you obsess about continuous validation and you know it’s not about AUROC on a test set and you deeply understand the interplay of intended use with model ...

make an impact. Job Responsibilities Develop mathematical models for the valuation of credit derivatives, structured lending facilities, and illiquid collateral Implement methodologies for model calibration and build analytics to manage model risk appetite Leverage machine learning, AI, and data analytics to enhance valuation methodologies and drive innovation Define … methodology for pricing adjustments, model limitations, parameter uncertainty, and liquidity reserves Monitor model performance metrics to ensure models behave as expected over time Design and develop software frameworks for analytics delivery to systems and applications Collaborate with front office trading desks, controllers, and model risk teams ...

turn complex challenges into working solutions. You look at a decisioning problem, ask what outcome we need, what data we have, and what model will work best design it and coordinate delivery with our offshore and client teams. You spot issues before they become problems, raise them, and solve … driven automation flows that respond to customer behaviour in real time Design integrations with marketing, commerce and service platforms to close the loop between model scores and actions Ensure automation is scalable, auditable, and aligned with consent and data governance requirements Delivery & Leadership Lead technical workstreams ...

relevant statistical or machine learning packages Hands-on experience with machine learning frameworks and approaches, including supervised learning, unsupervised learning, feature engineering, modelselectionand model validation Practical experience building Generative AI and LLM-based solutions, including prompt engineering, embeddings, vector databases, RAG, grounding, reranking and evaluation Experience with … techniques such as text classification, entity extraction, semantic similarity,summarisationand information retrieval Experience using Databricks, Spark andlakehouseconcepts for large-scale data preparation,experimentationand model development Familiarity with Microsoft Fabric, Azure AI services, Azure Machine Learning or comparable cloud-based AI and data science platforms Experience withMLOpspractices including Git, automated ...

relevant statistical or machine learning packages Hands-on experience with machine learning frameworks and approaches, including supervised learning, unsupervised learning, feature engineering, modelselectionand model validation Practical experience building Generative AI and LLM-based solutions, including prompt engineering, embeddings, vector databases, RAG, grounding, reranking and evaluation Experience with … techniques such as text classification, entity extraction, semantic similarity,summarisationand information retrieval Experience using Databricks, Spark andlakehouseconcepts for large-scale data preparation,experimentationand model development Familiarity with Microsoft Fabric, Azure AI services, Azure Machine Learning or comparable cloud-based AI and data science platforms Experience withMLOpspractices including Git, automated ...

relevant statistical or machine learning packages Hands-on experience with machine learning frameworks and approaches, including supervised learning, unsupervised learning, feature engineering, modelselectionand model validation Practical experience building Generative AI and LLM-based solutions, including prompt engineering, embeddings, vector databases, RAG, grounding, reranking and evaluation Experience with … techniques such as text classification, entity extraction, semantic similarity,summarisationand information retrieval Experience using Databricks, Spark andlakehouseconcepts for large-scale data preparation,experimentationand model development Familiarity with Microsoft Fabric, Azure AI services, Azure Machine Learning or comparable cloud-based AI and data science platforms Experience withMLOpspractices including Git, automated ...

requirements into analytical solutions and actionable insights. Experience creating dashboards, self-service reporting, and visualisations that support decision-making. Desirable: Experience with data governance, model management, and analytics best practices. Professional certifications in data management, analytics, business intelligence, or related disciplines (e.g. DAMA International or equivalent). This ...

technical hardware-and-software architect role, not a strategy-only position. The successful candidate operates comfortably across GPU infrastructure, high-performance networking, model training and inference pipelines, and the AI risk/governance disciplines increasingly demanded by regulators and enterprise boards. The Enterprise Architect will lead technical delivery teams … inference/serving platforms, MLOps/LLMOps tooling, vector databases, and retrieval-augmented generation (RAG) and agentic architectures. Define and AI governance frameworks covering model risk management, responsible AI, data lineage, bias/fairness testing, explainability, and regulatory alignment (EU AI Act, NIST AI RMF, ISO/ ...

analysis (regulatory and economic) for Chaucer’s managed Lloyd’s syndicates. Delivery of the syndicate SCR, taking responsibility for specific areas of the internal model, producing and validating model outputs. Involved in model and MI development as well as use of the capital model throughout … decisions as required;* Produce and develop management information for the interpretation and presentation of modelled results to various groups within Chaucer, including Risk and Model Working Groups and ad-hoc forums with senior management as required* Assist in the ongoing development (incl. Igloo coding) and parameterisation of the Internal ...

London to join the Market Data and Integration team within Risk Analytics. The role will focus on workflow design, data pipeline requirements, integration patterns, validation controls, and operational improvements that support scalable risk analytics delivery. Responsibilities The Senior Product Analyst will work with product, financial engineering, data, technology, support … professional services, and client-facing teams to analyse requirements and design robust workflows for market data ingestion, enrichment, validation, transformation, integration, and delivery into Risk Analytics products and services. The role will translate business, analytical, and operational needs into clear specifications, data mappings, process flows, user stories, acceptance criteria ...

experience designing, building, and operating reliable data platforms, pipelines, and data products. We are especially interested in people who understand data modelling, data quality, validation, observability, cost control, and how to make data trustworthy for technical and non-technical users. Technical Skills: Languages: Python, SQL, C#, Golang, Java, Kotlin ...

within Investment Banking or Global Markets environments. Experience testing workflow, task management or case management systems. Exposure to AI, Machine Learning or Large Language Model solutions. Experience validating AI-driven classification, routing or decision-making workflows. Experience with Oracle, Hadoop and Elasticsearch. Familiarity with observability and monitoring platforms. Knowledge ...

seamless integration across platforms. Analyse large data sets for anomalies or control gaps while maintaining data integrity across all surveillance and reporting systems. Support model validation processes including tuning machine learning models where applicable to enhance detection capabilities. Participate actively in change management activities such as system upgrades …/documentation purposes. Exposure to AI/ML frameworks such as TensorFlow or PyTorch along with practical experience deploying models into production environments; understanding model lifecycle management/monitoring processes. Previous involvement with transaction monitoring systems (e.g., Actimize), sanction screening tools (e.g., Fircosoft), communication surveillance or market/trade ...

deliver measurable business impact. Design and enhance margin and derivative models, including methodology selection, calibration, numerical schemes, benchmarking/backtesting, documentation, and alignment with model risk governance. Serve as model owner: manage roadmaps, controls, monitoring/alerts, change management, and responses to Model Risk, Audit, and regulatory … reviews; ensure explainability and transparency of assumptions, limitations, and model performance. Build and productionize analytics that advance intraday/EoD automation (services, APIs, pipelines) with clear SLOs/SLA, observability, reliability engineering practices, and tight integration into trading/risk platforms. Provide technical leadership and mentorship; conduct code/ ...

management across Front Office, Risk, Technology, and Finance. Demonstrated ability to combine strategic thinking with practical execution. Deep experience working with Quants, Market Risk, Model Validation, and regulatory stakeholders. Robust technical grounding, with the ability to rapidly understand highly‐detailed architectures, data flows, and system integrations. Experience across ...

management across Front Office, Risk, Technology, and Finance. Demonstrated ability to combine strategic thinking with practical execution. Deep experience working with Quants, Market Risk, Model Validation, and regulatory stakeholders. Robust technical grounding, with the ability to rapidly understand highly‐detailed architectures, data flows, and system integrations. Experience across ...

emerging area, so part of the role will be to shape the problem space by working with other teams to find, validate and model useful signals for participant quality. The ideal candidate will help define the right problems to solve, not just execute against a fixed brief. The Applied ...

environment. The Data Scientist role suits a hands-on Data Scientist who is comfortable working across the full lifecycle from data exploration through to model development validation plus deployment support. Responsibilities for the Data Scientist: Develop statistical models machine learning solutions analytical frameworks to address complex business problems … outputs into clear insights recommendations for technical non-technical stakeholders Work closely with data engineers analysts to ensure models are production-ready scalable Validate model performance manage bias ensure outputs are robust explainable reliable Contribute to continuous improvement of data science practices tooling governance Essential Skills for the Data ...

platforms Develop and apply data quality frameworks to assess and ensure fitness-for-purpose of diverse data sources for specific analytical questions Implement strong model evaluation practices including cross-validation strategies, calibration assessment, and transparent reporting of model performance and limitations Build scalable, automated processes for delivering … health data and wearable/sensor-derived data types Experience with cloud-based scalable compute and deployment patterns for large-scale data processing and model training #LI-Hybrid If you come across a role that intrigues you but doesn’t perfectly line up with your resume, we encourage ...

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 ...

Financial Risk Management (FRM) team, where we develop, validate, and enhance the methodologies that underpin Swiss Re's financial risk framework. Our Financial Model Validation & Methodologies team, based in London, Zurich, and Bangalore, works at the intersection of risk management, actuarial science, finance, and technology to strengthen Swiss … methodologies. Enhance risk systems to reflect evolving portfolio characteristics, market dynamics, and regulatory requirements. Contribute to the integrity of Swiss Re's Internal Capital Model, ensuring methodologies remain robust, transparent, and fit for purpose. Serve as a subject matter expert on market and credit risk methodologies, providing advice ...