26 to 50 of 373 Model Validation Jobs in the UK

technical leadership and mentorship to fellow data scientists, elevating the team's capabilities and fostering a culture of excellence. Own the end-to-end model lifecycle, from initial R&D and prototyping through to deploying robust, scalable models into production pipelines. Partner with senior stakeholders across Product, Sales … Leadership to translate complex business needs into elegant, effective analytical solutions. Champion best practices in model development, validation, and maintenance to ensure the quality and integrity of our analytical outputs. Job Qualifications: We are seeking an exceptional technical leader. We strongly encourage applications from candidates with a background ...

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 ...

integrating previous pre-trained models with simulations or other advanced modelling. Additional skills and experience necessary for the role Awareness of different solutions for model management that includes model building and deployment. Determines and executes model validation, reproducibility, and deployment criteria. Ability to get results fast ...

integrating previous pre-trained models with simulations or other advanced modelling. Additional skills and experience necessary for the role* Awareness of different solutions for model management that includes model building and deployment.* Determines and executes model validation, reproducibility, and deployment criteria.* Ability to get results fast ...

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 ...

everyday lives of people around the globe. An exciting opportunity has arisen for a HiL Development & Test Engineer to support the development, integration, and validation of advanced automotive systems within a cutting-edge Hardware-in-the-Loop (HiL/XiL) environment. This role focuses on the design, configuration, delivery … single ECU setups through to complex multi-ECU architectures incorporating up to 30 ECUs in the loop. The successful candidate will contribute to the validation of Advanced Driver Assistance Systems (ADAS) and Advanced Automated Driving (AAD) features through both signal-based and scenario-based testing methodologies. Working within ...

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 ...

leader in AI-powered drug discovery. Core accountabilities Own and lead the AI Accelerator as the single consolidated machine learning, deep learning and foundation-model capability serving every in silico unit, comprising the Machine Learning, Generative & Agentic AI, and Therapeutic Hypotheses groups Set the technical AI vision and multi … year roadmap for AI-powered drug discovery at Evotec, and translate the In Silico & AI strategy into a prioritised model and capability portfolio Deliver predictive models for molecular property, activity, ADMET and safety at a quality and scale that individual science units could not build or maintain alone Deliver ...

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 ...

doing: · Develop and enhance reporting, dashboards and analytical products that provide insight to senior business leaders and customers. · Centralise, cleanse, validate and model data from multiple business systems within modern data platforms and data lake environments. · Build and maintain data pipelines, automated solutions and analytical tools using technologies including ...

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 ...

inclusive employer and a member of myGwork – the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. 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 … Model Governance Director, Data Science, you will own and evolve the end-to-end AI and model governance framework on behalf of the Data Science function. You will provide strategic leadership, helping to ensure AI systems are developed and deployed responsibly while balancing regulatory compliance, risk management, innovation ...

systems, etc.), Selecting and optimizing algorithms (regression, tree-based models, neural networks, etc.), Integrating models into production environments, Performing data cleaning, feature engineering, and model validation, Identifying tools and specifying processes Mentoring junior team members and contributing to solution architecture, Preparing and presenting analytical results to business … team growth. What We Offer Opportunity to work on cutting-edge AI and ML projects, Collaboration with international clients (US and Europe), Hybrid working model – 3 days per week in the office, with the option to work remotely on the remaining days, Supportive, innovation-driven work environment focused ...

their AI, models, and data are sound, controlled, and compliant. The company delivers end-to-end audits of AI systems, including AI vendor dependencies model risk and validation, AI controls, data lineage and provenance, and regulatory readiness for frameworks such as the EU AI Act, DORA, and GDPR. … contingent fee arrangements. Role Description This is a part-time AI Advisory Board role based in Greater London with a hybrid working model, combining in-person meetings with some work from home. Advisory Board members provide strategic guidance on AI assurance, governance, and risk management, contributing to board-level ...

implementing Ahead-of-Time or Just-in-Time compilation flows for AI workloadsTransforming graphs or working with operator partitioning, scheduling, memory planning, or model optimisationValidating, benchmarking, profiling, or analysing AI model performanceDeveloping compiler technologies, intermediate representations, or hardware abstraction layersBuilding automated tests and CI/CD workflows … expertise in machine learning runtime development and hardware-accelerated AI execution. The work spans the end-to-end AI software stack, from framework-level model execution and backend delegation through compiler flows to NGP acceleration.Working collaboratively across Arm provides exposure to inference engines and runtimes, accelerator integration, operator partitioning ...

implementing Ahead-of-Time or Just-in-Time compilation flows for AI workloads Transforming graphs or working with operator partitioning, scheduling, memory planning, or model optimisation Validating, benchmarking, profiling, or analysing AI model performance Developing compiler technologies, intermediate representations, or hardware abstraction layers Building automated tests … machine learning runtime development and hardware-accelerated AI execution . The work spans the end-to-end AI software stack, from framework-level model execution and backend delegation through compiler flows to NGP acceleration. Working collaboratively across Arm provides exposure to inference engines and runtimes, accelerator integration, operator partitioning ...

implementing Ahead-of-Time or Just-in-Time compilation flows for AI workloads Transforming graphs or working with operator partitioning, scheduling, memory planning, or model optimisation Validating, benchmarking, profiling, or analysing AI model performance Developing compiler technologies, intermediate representations, or hardware abstraction layers Building automated tests … machine learning runtime development and hardware-accelerated AI execution . The work spans the end-to-end AI software stack, from framework-level model execution and backend delegation through compiler flows to NGP acceleration. Working collaboratively across Arm provides exposure to inference engines and runtimes, accelerator integration, operator partitioning ...

learning and experimentation.Advanced Python programming skills.Experience developing deep generative models, including transformers, diffusion models, GANs or VAEs.Experience building applications using Large Language Models.Knowledge of model validation, evaluation frameworks and MLOps practices.Experience working with cloud platforms such as AWS, Azure or Google Cloud.Ability to influence stakeholders and communicate complex ...

commercial outcomes. You'll work across: Customer segmentation, propensity modelling and churn prediction. Revenue and demand forecasting. Python-based modelling, feature engineering and model validation. Production deployment, cloud infrastructure and MLOps. Translating complex analysis into actionable commercial insights. Collaborating with product, engineering and client teams to develop AI-powered ...

into enterprise applications. Create reusable AI components and frameworks. Machine Learning Engineering Train, fine-tune, evaluate, and deploy ML models. Develop feature engineering and model evaluation pipelines. Implement model monitoring and performance tracking. Optimize model inference performance and cost efficiency. Develop LLM-based applications and workflows. Build … knowledge retrieval systems. Design evaluation frameworks for AI quality, safety, and reliability. Improve hallucination mitigation and response accuracy. MLOps & Deployment Design and automate ML model training, validation, and retraining pipelines. Version and manage datasets, features, and model artefacts using tools such as MLflow or similar. Deploy ...