126 to 150 of 230 Model Validation Jobs in England

tools robust to the heterogeneity of operating room environments, so that customers all over the world can benefit from tailored solutions. Own the full model lifecycle including data curation, model implementation, training, validation, deployment and maintenance. Develop within Proximie environment to enable dynamic model training ...

customised neural networks, training strategies, loss functions and evaluation metrics. Implement and adapt techniques from recent AI and computer vision research. Build scalable training, validation, evaluation and inference pipelines. Optimise models for accuracy, robustness, latency and deployment across cloud and edge platforms. Translate research outputs into maintainable, production-quality … experience will also be considered. Strong knowledge of CNNs and modern computer vision techniques. Experience designing, modifying or adapting neural network architectures. Experience with model training, validation, hyperparameter optimisation and performance evaluation. Experience implementing techniques from recent AI or computer vision research. Experience delivering reliable AI systems into ...

Deep grounding in statistics, machine learning, time-series analysis, and predictive modelling, with experience building models underreal operationalconstraints. Hands-on ownership of the full model lifecycle: data exploration, feature engineering, model development, back-testing, validation, deployment, monitoring, and ongoing tuning. Extensive experience working with large, complex … including missing data, outliers, regime changes, noisy labels, and evolving schemas. Strong understanding of production ML system design, including batch vs real-time inference, model serving patterns, performance trade-offs, and failure modes. Experience operating models in production over time, including versioning, drift detection, retraining strategies, and incident response ...

statistics, machine learning, time-series analysis, and predictive modelling, with experience building models under real operational constraints. Hands-on ownership of the full model lifecycle: data exploration, feature engineering, model development, back-testing, validation, deployment, monitoring, and ongoing tuning. Extensive experience working with large, complex, and imperfect … including missing data, outliers, regime changes, noisy labels, and evolving schemas. Strong understanding of production ML system design, including batch vs real-time inference, model serving patterns, performance trade-offs, and failure modes. Experience operating models in production over time, including versioning, drift detection, retraining strategies, and incident response ...

join its Liquidity and Market Risk team in London with hybrid working (2 days in the office). The role focuses on stress testing, model ownership, validation-style testing and deeper analysis of model algorithms, code and data. You will monitor and govern risk models, test assumptions … develop benchmarking models. A strong technical and quantitative background in model risk, validation or governance is essential. #J-18808-Ljbffr ...

integration, and AI/ML featuresTest AI/ML applications and machine learning models from a product and user perspectiveEvaluate AI/ML model outputs for correctness, consistency, and expected application behaviorDefine structured rubrics that translate qualitative findings into measurable evaluation gatesBuild quality gates for CI/… design patternsAbility to work in an Agile development environmentPreferred Qualifications Experience testing AI/ML applications or validating machine learning modelsExperience with data validation tooling (e.g., Great Expectations) or labeling workflowsFamiliarity with ML frameworks (e.g., PyTorch, TensorFlow)Experience with data pipelines and orchestration tools (e.g., Airflow, Metaflow)Knowledge ...

integration, and AI/ML featuresTest AI/ML applications and machine learning models from a product and user perspectiveEvaluate AI/ML model outputs for correctness, consistency, and expected application behaviorDefine structured rubrics that translate qualitative findings into measurable evaluation gatesBuild quality gates for CI/… design patternsAbility to work in an Agile development environmentPreferred Qualifications Experience testing AI/ML applications or validating machine learning modelsExperience with data validation tooling (e.g., Great Expectations) or labeling workflowsFamiliarity with ML frameworks (e.g., PyTorch, TensorFlow)Experience with data pipelines and orchestration tools (e.g., Airflow, Metaflow)Knowledge ...

integration, and AI/ML featuresTest AI/ML applications and machine learning models from a product and user perspectiveEvaluate AI/ML model outputs for correctness, consistency, and expected application behaviorDefine structured rubrics that translate qualitative findings into measurable evaluation gatesBuild quality gates for CI/… design patternsAbility to work in an Agile development environmentPreferred Qualifications Experience testing AI/ML applications or validating machine learning modelsExperience with data validation tooling (e.g., Great Expectations) or labeling workflowsFamiliarity with ML frameworks (e.g., PyTorch, TensorFlow)Experience with data pipelines and orchestration tools (e.g., Airflow, Metaflow)Knowledge ...

proportionate, business-relevant advice, assurance and audit services. This role is responsible for leading and delivering specialist services in data governance, AI governance, AI model testing, and data analytics audits across Financial Services clients. As an Associate Director, you will act as a recognised subject matter expert across client … look into the role As an Associate Director within BRS, you will: Own and lead complex client engagements across data governance, AI governance, AI model testing, and analytics internal audit/risk within Financial Services, managing a significant portfolio of client relationships at senior stakeholder level. Lead strategic planning ...

shortfall and stress test calculations. This includes testing scenario design, implementation, results consolidation, and analyses of calculations to understand key driversInvestigate data issues and model anomalies, expanding and debugging the existing risk and PnL calculation code, and improving performance and maintainabilityPartner with Tech, Quants and Risk partners to ensure … that the solutions are scalable and aligned with the programmes’ needsDrive continuous improvement through critical review of model development and validation outcomes, and constructive challenge and feedback on technical documentationRequired Qualifications and Skills:Masters/PhD level in a quantitative subject (Mathematics, Statistics, Physics, Engineering, Computer Science ...

management skills, with the credibility to engage senior business and technical buyers. Hands‐on experience applying machine learning to real-world business problems, including model selection, configuration, tuning, and evaluation. Strong Python and SQL skills, with the ability to work confidently in notebooks and against large data sets during … fraud, or KYC. Strong candidates from adjacent regulated domains will also be considered, provided they can demonstrate the ability to ramp quickly. Understanding of model governance, validation and regulatory expectations in a financial crime setting (for example, OCC 2011‐12, SR 11‐7, EBA model risk guidance ...

Sompo Holdings, Inc. in London is looking for an AVP, Risk Modeling to lead catastrophe model validation, change, and implementation efforts. You will document methodologies, assumptions and testing, and work with Portfolio Analytics to translate results into actionable insights for underwriters. You will also drive system and reporting ...

prototyping; set review standards for AI‐generated code. Design, build, and maintain data engineering workflows and platform services supporting the Vision platform and model delivery ecosystem Develop and extend platform components responsible for data ingestion, transformation, validation, and routing across internal and external systems Build robust Python-based …/CD pipelines and deployment processes to ensure reliable and repeatable releases. Ensure data quality, auditability, and observability through logging, monitoring, lineage tracking, and validation frameworks Collaborate closely with investment teams to translate portfolio construction, risk, and analytics requirements into scalable technical solutions. Continuously improve the platform through modern ...

compute, memory, interconnect, and communication behaviour across large-scale ML systems Develop tools to simulate training and inference workloads across distributed accelerator clusters Model distributed execution patterns including collectives, synchronisation, and communication bottlenecks Run experiments and benchmarks on real ML systems to calibrate and validate simulation models Analyse ...

throughout the project lifecycle. Review consultant and subcontractor models to ensure quality, accuracy and buildability. Support project delivery through design coordination, technical reviews and model validation. Mentor and support BIM Coordinators and junior team members. Drive continuous improvement in BIM processes and digital construction methodologies. Requirements Previous experience ...

principles into architecture patterns and delivery processes Define runtime controls, monitoring, traceability and human-in-the-loop governance mechanisms Support AI inventory management, model governance and architectural traceability Contribute to AI risk assessments, threat modelling and regulatory alignment activities Ensure alignment with emerging regulatory frameworks including … integration architecture Enterprise security and identity models Threat modelling and AI governance Observability and operational monitoring patterns Structured and unstructured data architectures Model lifecycle management and AI operationalisation DevSecOps and platform engineering principles Applied data science techniques (classification, clustering, NLP) Model lifecycle management (training, validation, monitoring) Translating ...

used by institutional clients. As an early member of a small, senior team, you will work end‐to‐end across research, prototyping, data engineering, model implementation, production systems, and client‐facing applications. This is a high‐ownership role for someone who is comfortable contributing wherever needed in a fast … empirical methods, and the application of these concepts in the investment industry. Familiarity with cloud infrastructure, containerisation, orchestration, and CI/CD for model deployment. Experience in building institutional‐grade analytical tools or dashboards for sophisticated end users. Prior experience in a startup or early‐stage technology environment. Compensation ...

commercially valuable outcomes. Responsible for developing deployable analytical solutions in partnership with Engineering teams, while not owning production infrastructure or application development. Key Responsibilities Model Development Design, develop and maintain statistical, probabilistic and simulation‐based models. Translate complex business questions into tractable modelling problems. Select appropriate modelling approaches based … analytical assets that can be reused as products, decision‐support tools or operational capabilities. Design and analyse experiments to evaluate interventions, operational changes and model effectiveness. Inference & Uncertainty Work effectively with incomplete, imperfect and evolving datasets. Develop approaches for estimating missing information and combining evidence from multiple sources. Quantify ...

strategic technology transformation.The Global Head of AI Operations (AI Ops) is a senior technical leader responsible for transforming the organization's legacy operations model into a modern, AI-driven, autonomous operations capability. This leader will empower a next-generation run function with tools to support operational excellence, cyber resilience … disciplined recovery through APAC and EMEA market hours.Oversee regional change activity to ensure production readiness, safe implementation, business alignment, and effective post-change validation across international platforms.Strengthen problem management discipline by ensuring recurring issues are identified, root causes are addressed, corrective actions are tracked, and operational risk is reduced ...

media related data, linking with full business resultsMMM & Strategic MeasurementLead the relationship with Burberry’s in-house MMM team; overseeing the brief, model inputs, validation and readoutTranslate MMM outputs into clear investment recommendations for Media and FinanceBuild the calibration loop between MMM and in-channel measurement, ensuring ...

exotic structuresEnhance and maintain libraries for pricing, risk, and hedging of complex productsPartner directly with trading desks and structuring teams to deliver quantitative solutionsAnalyse model performance, calibrate to market data, and ensure robust risk management frameworksContribute to the evolution of model architecture, analytics, and trading toolsSupport model governance, validation, and regulatory requirements where applicableRequirementsAdvanced degree (PhD/MSc) in Mathematics, Physics, Engineering, or a highly quantitative disciplineSignificant experience within equity derivatives modelling, ideally with a focus on exoticsStrong understanding of: Stochastic calculus, PDEs, and numerical methodsVolatility modelling (local vol, stochastic vol, hybrid models)Proficiency ...

explainability, contestability, privacy, safety, security, robustness, human oversight and monitoring. Conduct AI and algorithmic impact assessments, including ethical risk, equality considerations, privacy, data protection, model/system risk, operational risk and potential harm. Define AI assurance approaches, including assurance cases, evidence requirements, model/system evaluation, testing, validation … governance structures, including AI boards, risk triage, decision rights, accountability models, approval gates and lifecycle controls. Support documentation and transparency activities, including model cards, system cards, assurance packs, risk assessments and Algorithmic Transparency Recording Standard submissions where relevant. Review AI-enabled products, vendor tools, automation solutions, decision-support systems ...

Scientist in London to join the Genomics team. You will define data needs for AI models, ensure high-quality ground truth, and validate foundational model success with rigorous evaluations. You will work with deep-learning, engineering, and translational teams to shape data requirements, provenance, and performance, contributing across ...

building design, including energy analysis, building performance, low-carbon design and net-zero strategies. Its BIM team also supports projects through 3D modelling, design validation, coordination, constructability review and performance analysis. For an Electrical Designer, that creates exposure to more than the electrical package itself. ...

documentation, and prototyping; set review standards for AI‐generated code.Design, build, and maintain data engineering workflows and platform services supporting the Vision platform and model delivery ecosystemDevelop and extend platform components responsible for data ingestion, transformation, validation, and routing across internal and external systemsBuild robust Python-based services …/CD pipelines and deployment processes to ensure reliable and repeatable releases. Ensure data quality, auditability, and observability through logging, monitoring, lineage tracking, and validation frameworksCollaborate closely with investment teams to translate portfolio construction, risk, and analytics requirements into scalable technical solutions. Continuously improve the platform through modern engineering ...