26 to 50 of 75 Model Validation Jobs in the UK

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/ ...

with production stability. Engineering & AI Execution Lead cross‐functional teams across engineering, data science, and ML engineering. Establish best practices for AI development, including model validation, monitoring, and retraining. Drive adoption of modern engineering standards (CI/CD, DevOps, automated testing). Ensure seamless collaboration between data, product … regulations and AI governance standards. Establish frameworks for ethical AI use, explainability, and bias mitigation. Partner with Legal and Compliance on data usage and model accountability. Maintain robust security practices across data and infrastructure layers. Leadership & Collaboration Build and scale high‐performing teams in engineering, AI, and data. ...

help deliver the efficiency, control, and transformation goals of the Bank. You will work within the wider GSA Control Strats team and lead model development across NS and TS. This includes supporting incumbent models and designing, building and deploying new state-of-the-art (SOTA) models. You will bring … strong data science and modelling expertise, a delivery-focused mindset, and a structured, detail-oriented approach to solving complex tasks. You will also drive model tuning, contribute to regulatory and governance deliverables, and collaborate with cross-functional teams including Anti-Financial Crime, Operations and Technology. You will work ...

platforms (Google CXAS/CES, Genesys, NICE, Amazon Connect) Experience in multi-agent orchestration/agentic frameworks Familiarity with AI governance, risk management, and model validation frameworks Certifications Google Cloud Professional Architect (Mandatory/Preferred) Google Professional Machine Learning Engineer Certifications in Conversational AI platforms (Google CES, Dialogflow ...

will be key to achieving success. Enterprise Architects: You will be responsible for defining and controlling the solution and system architecture (including models, decisions, validation, evolution, and delivery support), working with the customer and any subcontractors to identify, trade-off and design the overall architecture. You will also assist ...

building resilient, high-performing AI systems AI Governance & Risk Drive responsible and ethical AI adoption through robust governance frameworks Oversee AI lifecycle management, including model validation, monitoring, and risk controls Ensure compliance with regulatory standards and third-party vendor requirements Collaboration & Enablement Work closely with engineering, data ...

rapidly evolving industry. SCOPE OF THE ROLE In this role as a Senior Machine Learning Engineer you will: Design and implement data ingestion, model training, validation, deployment and monitoring pipelines across the organization Optimize ML infrastructure and systems for maintainability, scalability, robustness, efficiency, and operating costs Collaborate with ...

rapidly evolving industry. SCOPE OF THE ROLE In this role as a Senior Machine Learning Engineer you will: Design and implement data ingestion, model training, validation, deployment and monitoring pipelines across the organization Optimize ML infrastructure and systems for maintainability, scalability, robustness, efficiency, and operating costs Collaborate with ...

clustering, regression, predictive analytics) with ability to take problems from framing through to deployment-ready outputs Must be strong in data exploration, feature engineering, model evaluation, and communicating insights clearly to non-technical stakeholders ideally within demand-led public services (predictive demand, prevention, triage/segmentation). Needs working ...

support to help members to develop their domain expertise. The System Architect is responsible for defining the solution and system architecture (including models, decisions, validation, evolution and delivery support), working with the customer and any subcontractors to identify, trade-off and design the overall architecture. Architects assist with ...

support to help members to develop their domain expertise. The System Architect is responsible for defining the solution and system architecture (including models, decisions, validation, evolution and delivery support), working with the customer and any subcontractors to identify, trade-off and design the overall architecture. Architects assist with ...

strongly encourage applications from people with diverse and underrepresented backgrounds and perspectives. Responsibilities 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 ...

language for the large-scale analysis and production of securities data Research and development of market dynamics across multiple asset classes Prototyping, testing, and validation of TradingHub’s proprietary models supporting and coaching more junior team members Requirements Proven financial markets experience, ideally within an investment bank or pricing ...

people with diverse and underrepresented backgrounds and perspectives. In this role you will 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 ...

predictive, analytical, and decisioning solutions. Use Python, Spark, and relevant data tools to clean, transform, explore, and analyse datasets. Support the development, testing, and validation of machine learning models, business metrics, dashboards, and decisioning logic. Apply foundational statistical and machine learning techniques to help solve business problems and improve … clarify assumptions, and translate problems into analytical tasks. Communicate analysis, methods, and results clearly through written summaries, visualisations, presentations, and documentation. Help validate data, model outputs, metrics, and reports to ensure results are accurate, reliable, and explainable. Contribute to scalable and repeatable data science processes, including data preparation, workflow ...

transition prototypes into production-ready systems . Develop and maintain end-to-end ML pipelines for data ingestion, training, testing, and deployment. Optimise model performance, scalability, and reliability using MLOps best practices. Work with large-scale structured and unstructured datasets for model training and validation. Implement model … . Experience with data engineering concepts — ETL pipelines, data lakes, and cloud data platforms. Proficiency with cloud services (AWS, Azure, or GCP) for model deployment and orchestration. Knowledge of containerization and orchestration tools (Docker, Kubernetes). Experience integrating ML models into production environments via APIs or microservices. Excellent problem ...

they can be applied to our products Operations: Optionally contribute to our AI infrastructure to help operate self-hosted open-source models Testing & Validation: Development of tooling to assist our Test Team in conducting evals against our many provider models to ensure we are continually optimising for quality ...

drug development programs. You will be accountable for building end‐to‐end clinical AI/ML solutions—from problem framing and data strategy, through model development and validation, to deployment and lifecycle management in production environments that support clinical trials and regulatory decision‐making. The AI/… powered products. Advanced Python programming skills and a track record of delivering robust software solutions. Proficiency with standard deep learning algorithms and model architectures. In depth knowledge in machine learning best practices, scalable training and deployment. Experience operating in cloud environments (e.g., Azure, AWS, or GCP). Strong product ...

Computer Science or a related quantitative discipline or BSc with >2 years of professional experience as a data scientist (or similar) Strong understanding of model development, validation , and deployment in research or production settings Able to deliver production quality data science code Able to work autonomously , quickly understand ...

extraction, plus concise text summarisation. Experience Requirements Core semantic/graph tech W3C standards and tooling: RDF, RDFS, SKOS, OWL, SHACL , SPARQL for modelling, validation and querying. Graph databases and platforms: GraphDB, Stardog, Amazon Neptune, Neo4j, TigerGraph, ArangoDB or similar RDF/LPG stores. Ontology and knowledge graph frameworks ...

mathematical formulation and numerical implementation to performance optimisation and direct contribution to live analytics and trading systems. What You Will Do End-to-End Model Ownership: Independently design, implement, and validate pricing and risk models for complex and exotic OTC derivatives (from math formulation to production rollout). Core ...

based backend applications and services, with a strong emphasis on REST API design and implementation using FastAPI. You will work with Pydantic for schema validation and SQLite for lightweight relational data storage, ensuring high-quality, maintainable, and well-tested code. The position requires close collaboration with a diverse team ...

looking to recruit for a Contract Data Analyst to join their client for an exciting position that combines data science with practical testing and validation activities. This is fulltime onsite role working in the offices 5 days a week and is OUTSIDEIR35. Key Responsibilities: Collect, manage, and maintain sensor … collection. Cleanse, validate, and quality-check data to ensure accuracy and integrity. Support the development, refinement, and testing of machine learning models. Conduct practical validation activities to assess model accuracy and performance. Compare model outputs against real-world test results and recommend improvements. Create and maintain Standard ...

stack including: SQL, Python, Power BI, Microsoft Fabric and Azure About the Opportunity You will begin with broad exposure across data systems, including testing, validation and analysis, before progressing into a more specialised data role. This approach builds a strong foundation and sets you up for long-term success. … similar reporting tools Basic knowledge of Python or DAX Exposure to Azure, Microsoft Fabric or cloud data platforms Awareness of data quality processes, validation or testing Experience or interest in financial services or regulated environments What You'll Be Doing Build and maintain reports and dashboards used across ...

define success metrics, guardrails, and decision frameworks, translating analytical results into actionable product and operational actions. Define and uphold engineering standards and guidelines for model development, including validation, uncertainty, reproducibility, and bias/quality checks. Drive scalable experimentation with A/B and Multi-armed bandit testing frameworks … variance reduction, and online-offline alignment. Work together with Data Engineering, MLOps, and Game Tech teams to guarantee dependable data foundations, feature accessibility, and model deployment pathways. Build internal data products to improve the speed and quality of decision-making, such as AB-test calculators, decision tools, and automated ...