1 to 25 of 189 Model Validation Jobs in 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 … strong understanding of AI model risk management, including risks and controls specific to Generative AI and agentic AI, and their implications for model validation and governance Practitioner-level agentic AI skills : a demonstrated track record of building, deploying and evaluating AI agents and multi-agent systems, including ...

# 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 ...

decode risk to unlock opportunity, helping our clients navigate uncertainty with clarity, speed, and confidence. Skills and Competencies A deep understanding of AI model risk management, including risks and controls specific to Generative AI and agentic AI, and their implications for model validation and governance Genuine, hands … such as R, Python, MATLAB, and SQL, with the ability to work within an established codebase; knowledge of C++ programming is preferred Experience in model validation, model risk management, or independent review is advantageous, with prior work in credit, counterparty, or market risk considered helpful context Typically ...

serve customers. As the use of Generative AI, Large Language Models (LLMs) and Agentic AI continues to expand, the need for robust governance, validation and oversight has never been greater. We are seeking an experienced AI specialist to join a growing AI Validation & Governance function in a high … profile Vice President role. Reporting directly to the Head of AI Validation & Governance, you will play a pivotal role in defining how AI models are independently assessed, challenged and governed across the organisation. This is a unique opportunity to help build the framework that will underpin the safe ...

Senior Decision Scientist - Validation £60,000 - £80,000 | London Are you a credit risk modelling specialist looking to move into a high-impact validation role within a fast-growing fintech? This is an opportunity to join a well-established business where data science and automated decisioning … They have built a highly data-driven lending platform powered by machine learning and automated credit decisioning. This role offers the opportunity to influence model governance and validation standards within a business where analytical insights directly shape commercial outcomes. THE ROLE As a Senior Decision Scientist within ...

About the Team Goldman Sachs's Model Risk Management (MRM) team plays a critical role in ensuring the safety and soundness of the firm's models. MRM validates a diverse set of models, including AI and machine learning models, used within the firm. This role offers the opportunity … make significant contributions to the firm's overall model risk management framework and AI. MODEL RISK MANAGEMENT (MRM) The Model Risk Management (MRM) group is a multidisciplinary group of quantitative experts at Goldman Sachs with a presence in New York, Dallas, London, Birmingham, Warsaw, Hong Kong ...

looking for a Senior Data Scientist to join our AMI group. This hands-on role combines Machine Learning, statistical modeling, Generative AI, RAG, model evaluation, and fine-tuning for enterprise AI applications. AMI supports commercial AI providers and on-premises models, with agents, MCP tools, and A2A interoperability delivered … anomaly detection to enterprise AI and agentic use cases. Develop and evaluate intent classification, semantic matching, agent/skill/tool ranking, and model-routing techniques; compare learned approaches with rules, embeddings, and LLM-based baselines. Use statistical modeling to estimate execution latency, token demand, inference costs, workload trends ...

data connections and deploy analytical, AI-enabled or customer-facing applications. Ensure the responsible, transparent and secure use of AI and GenAI, including appropriate model validation, documentation, reproducibility, data governance and risk management. Establish and track KPIs, model performance measures and success metrics for predictive modelling … science innovation. Develop and maintain comprehensive documentation of models, methodologies and analytical frameworks to ensure reproducibility, auditability and knowledge transfer across the team. Optimise model performance and scalability, ensuring analytical solutions can handle increasing data volumes and computational demands across the R&D portfolio. Manage stakeholder relationships and provide ...

Monzo is hiring a Credit Model Validation Manager in the UK to provide independent validation and oversight across our credit modelling suite. You will lead hands-on validation of models used for customer-level decisioning, including ML/decision science and NPV models. You’ll work … purpose and well-governed. The role offers hybrid UK working options and a generous learning budget, with modern tooling and opportunities to influence model #J-18808-Ljbffr ...

using machine learning, statistical methods and natural language processing, where appropriate.• Apply quantitative analysis to support scenario assessments, thematic reviews and stress testing.• Ensure model outputs are explainable, validated and compliant with internal governance standards.Data Management and Quality Assurance• Ingest, clean and transform datasets from internal systems (e.g. … Compliance• Ensure analytical activities comply with applicable risk management frameworks, data governance standards and regulatory requirements.• Maintain appropriate documentation, controls and evidence to support model validation, audit and regulatory scrutiny.• Escalate material data quality issues, analytical limitations and risks to relevant stakeholders.Skills and ExperiencePriority Skills • Data Science ...

through PoCs, PoVs, MVPs, and, where appropriate, first production versions, before handing proven solutions to Solutions Engineering for scale-up — bringing to GSK a model proven by AI-native companies such as Anthropic, Palantir, and OpenAI. You will act as the most senior technical authority in the FDE function … portfolio of business stakeholders.Understanding of hands-on expertise in GenAI patterns, including agents, multi-agent orchestration, RAG, prompt engineering, evaluation, fine-tuning, and Model Context Protocol (MCP) integrations.Enterprise-level expertise in AI, ML, and data science — classical ML, deep learning, LLMs and foundation models, statistical and causal inference ...

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. ...

Palantir, OpenAI) or hyperscaler.Experience in regulated industries (pharma, healthcare, financial services) and familiarity with GxP, GDPR, and SOX.Working knowledge of fine-tuning fundamentals and Model Context Protocol (MCP) integrations.Track record of contributing reusable engineering patterns that others have adopted.About GSK Enterprise AIEnterprise AI is GSK's centre of gravity … Frameworks, Computer Programming, Data Preprocessing, Deep Learning, Google Cloud Platform (GCP) for Machine Learning, Machine Learning Algorithms, Microsoft Azure Data and AI, ML Frameworks, Model Evaluation, Model Training, Model Validation• If you are based in Cambridge, MA; Waltham, MA; Rockville, MD; or San Francisco ...

great and versatile role, looking for a Quantitative Developer to join the team responsible for maintaining and enhancing Derivatives risk – Initial Margin Model (IMM) and related analytics infrastructure. This role combines quantitative expertise with strong programming skills to deliver robust, efficient, and scalable solutions for margin calculation and risk … institution. This is a Technical Quant Development role requiring someone with some years exposure in either Derivatives Margin Modelling (preferable), Capital Markets Risk modelling, Model Validation, Model development experience and now looking to take their career forward in a more industry leading way. #J-18808-Ljbffr ...

processes, onboarding, and governance**Digital Delivery Oversight/BIM Execution Governance*** Provide governance over BIM/Digital Delivery teams to ensure consistent execution of:* Model federation and coordination* Clash detection and resolution workflows* Geometry QA and model health monitoring* Naming compliance and Revit standards* Level of Development … definition and compliance* View templates and publishing workflows* Navisworks coordination* Discipline model management and consultant integration* Additionally, ensure implementation of:* BIM model auditing frameworks* Geometry compliance validation* Model coordination control* LOD validation and reporting**Lifecycle Digital Asset Integration*** Establish and govern the EMEA digital asset ...

based architectures. Define the technical vision for AI products, ensuring solutions are scalable, secure, maintainable, and aligned with business objectives. Provide deep expertise in model development, experimentation, optimization, evaluation, and production deployment. Establish standard methodologies for LLM evaluation, model benchmarking, AI quality measurement, and performance assessment. Evaluate emerging … technologies, foundation models, and third-party solutions to find opportunities for innovation and business value. Guide architectural decisions across AI platforms, model-serving infrastructure, data pipelines, and MLOps/LLMOps capabilities. Partner closely with Engineering teams to productionize AI solutions and drive operational excellence. Build, mentor, and lead high ...

analytical tools for HEOR, primarily using R and C++. Support the development of cost-effectiveness and budget-impact models for health technologies. Contribute to model conceptualisation, implementation, validation and troubleshooting. Conduct analyses of healthcare, clinical trial and other relevant data. Critically review model structures, inputs, assumptions … health systems and HTA processes. Experience of healthcare data analysis or clinical trial interpretation. Experience of consulting or other client-facing work. Familiarity with model validation, quality assurance and technical documentation. Experience of teaching, training or communicating technical concepts. Knowledge of additional programming languages, including C++, would ...

Model Governance Director, Data Science Are you passionate about building and owning practical, scalable AI governance frameworks that enable innovation while managing risk? About the Role As Model Governance Director, Data Science, you will own and evolve the end-to-end AI and model governance framework … closely with technical, legal and product stakeholders to embed effective governance into how we use AI. Responsibilities Own the end-to-end AI and model governance framework on behalf of the Data Science function, including policy implementation and continuous improvement. Define standards for model risk classification, approvals, documentation ...

data formats, as well as mining external data, with the aim of utilizing them for the purpose of predictive and prescriptive modelling solutions. Data Validation This role is responsible for ensuring that the data being used is accurate, reliable, and suitable for the model being built. This includes … tasks such as data cleaning, data verification, data transformation and validation methods using both statistical and machine learning methods. Model Usage This role assists with marrying business understanding and knowledge with existing, appropriate, predictive and prescriptive model offerings (machine learning and AI) for commercial and/ ...

companies to drive transformation, meet the challenges of our industry and ensure we stay relevant and resilient. This partnership is a unique, industry-first model which brings together the best of in-house and 3rd party capability. We work with customers across 28 countries from 10 VOIS locations: Albania … LLMs), Small Language Models (SLMs) and predictive models. The successful candidate will lead high-value experimentation and pilot delivery, providing deep technical leadership across model engineering, data science, vendor strategy and AI innovation while working closely with product and platform teams to enable scalable solutions. Lead the strategy ...

world of siloed and disconnected data bringing context to the disparate views of similar data Undertake exploratory data analysis, data preparation, feature engineering and model development using appropriate programming languages, tools and analytical techniques Apply statistical analysis, predictive modelling, classification, natural language processing and other relevant techniques to address … range of business challenges Evaluate and communicate model performance, limitations, assumptions and potential risks, ensuring proposed solutions are appropriate for their intended business use Present technical findings and outcomes to both technical and non‐technical stakeholders, clearly articulating potential business value and recommendations Support the development of data science ...

used to mitigate fraud risk within ICB. You will work with multiple partner teams—including Strategy, Technology, Product Management, Legal, Compliance, Business Management, and Model Governance — to ensure the models meet the firm’s high governance standards and regulatory requirements, and support audit and other business functions around model … leading vendors for detecting and preventing fraudulent activities. Job Responsibilities Develop and manage proprietary fraud models and perform due diligence for vendor models. Validate model performance on internal data, ensure modelling choices are appropriate for the portfolio, decisioning context, and operational constraints. Work closely with platform engineers to support ...

predictive modelling and optimization to complex business problems. Design analytical approaches for large and complex datasets. Develop, validate and optimize ML models. Establish robust model validation and performance measurement frameworks. Translate analytical outputs into actionable business recommendations. Guide Data Scientists in selecting appropriate modelling approaches based on business ...

primary focus in either production quantitative engineering or applied quantitative modelling Python implementation of quantitative work from research or prototype through reliable production use Validation, backtesting and monitoring of model and service performance against realised outcomes Deployment, incident response, root-cause analysis and continuous improvement with stakeholders Shared … systems Where you’ll grow Market data management and onboarding new pipelines.. Designing new quant infrastructure and systems with the engineering team. Backtesting frameworks, model validation and risk modelling alongside the Risk team (VaR, stress testing, scenario analysis). Customer behaviour modelling, pricing strategy and product development. Collaborating ...

financial services business. The role will focus on developing and delivering data science solutions across the full machine learning lifecycle, from data preparation and model development through to deployment and monitoring. Working closely with technical teams and commercial stakeholders, the successful candidate will use data science to solve business … MLOps. Previous production experience is not essential, as training and development will be provided.Key Responsibilities• Deliver data science projects covering data preparation, exploratory analysis, model development and validation.• Contribute to the deployment and ongoing monitoring of machine learning models.• Take increasing ownership of the full model lifecycle.• Apply ...