76 to 100 of 155 Model Validation Jobs in the UK

guidance, including the EU AI Act, NIST AI Risk Management Framework, ISO/IEC 42001 and ISO/IEC 23894. Conduct AI risk assessments, model governance reviews, algorithmic impact assessments and responsible AI evaluations. Support AI lifecycle governance across model development, validation, deployment, monitoring, explainability, transparency, accountability … human oversight. Advise organisations on the governance implications of Generative AI, including data usage, intellectual property, security, privacy, bias and model risk. Facilitate workshops, governance forums and risk assessments with senior client stakeholders. Develop tailored AI governance approaches based on client business models, strategic objectives and regulatory requirements. Work ...

ANSYS Fluent, or Python. Strong background in heat and mass transfer, reaction engineering, and first-principles modelling (PDEs, reaction kinetics, etc.). Experience in model validation with lab or pilot data; understanding of solid–gas systems (calcination, hydration, carbonation); and past-demonstration of system optimisation preferred. Specifics ...

proven track record with at least some of these essential skillsets: Systems Engineering disciplines Problem definition Systems Architecture Synthetic Environments Performance Modelling Verification and Validation System of Systems Domain specialisms Digital signal processing RF systems Multi‐sensor data fusion and tracking Real time data simulation/generation Technical expertise ...

scale models through the full Software Development Life Cycle into production (including both ML and GenAI services).Perform exploratory data analysis, proof-of-concepts, model benchmarking, and validation experiments for both ML and GenAI approaches.Partnering with business leaders, domain experts, and end-users to gather requirements and align ...

tissue characterisation, and semantic segmentation design and build the data pipelines that turn raw clinical recordings into structured, governed training datasets, supporting continuous training, model improvement, and re-validation cycles architect and operate the production ML stack, including model versioning, deployment, monitoring, drift detection, and rollback … cloud-enabled, regulatory-cleared surgical imaging platform establish and maintain MLOps best practices, including reproducible training, dataset governance, experiment tracking, model documentation, that scale across multiple algorithms, sensors, and clinical indications mentor more junior research scientists and engineers identify and surface novel features in support of patenting activities work ...

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 ...

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 ...

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 ...

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 ...

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. ...

Principal Technical Specialist - Simulation (R&T) to lead the development of plant models for electrical motors, power electronics, batteries and mechanical components in a model-based simulation environment. You will optimize parameters to meet flight-cycle requirements and validate models using test data. You will provide technical guidance, contribute ...

lead the development of plant models for electric propulsion systems and power electronics. You will work in a fast-growing R&T team, building model-based simulations in MATLAB/Simulink to optimise performance of e-motors, gearboxes, batteries and power electronics. You will validate models with rigorous testing ...

validate models and decision logic (primarily in Python) to de-risk delivery, resolve ambiguous requirements with data, and partner with core Quant on model development and validation Build backtesting and analytics capability to assess strategy performance and support evidence-based enhancement prioritisation Lead end-to-end delivery ...

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. Location New York … London, Paris, Frankfurt About the team The Methodology and Model Development Group (MMDG) at Moody’s Ratings develops all the methodologies and analytical tools used in the rating process. The team is a critical contributor to Moody’s Ratings methodologies across all sectors. The Modelling and Quantitative Analytics Group ...

materials for senior risk forums Prototype and build analytical solutions using Python and automation frameworks Manage the full analytics lifecycle, including problem definition, prototyping, validation, and scaling Leverage AI-assisted tools to accelerate delivery while maintaining quality and governance standards Develop and validate credit loss models including probability … functional teams Preferred qualifications, capabilities, and skills Experience with solution architecture for analytical or risk platforms and familiarity with governance and control frameworks for model risk Hands-on experience applying AI or machine learning methods to credit analytics and decision support Experience working with technology teams to scale models ...

ingest, transform and process large and complex data sources. This can include automated web scraping and bulk data acquisition workflows. Implement data transformation, validation, and quality controls to ensure datasets are reliable, reproducible and analysis ready. Build and maintain containerised data and analytics applications (such as dashboards and data … quality Python code to work with complex or messy datasets. ( Lead Criteria) Understanding of core data engineering best practices, such as data-modelling, transformation, validation, testing, and reproducibility. Experience working collaboratively within multidisciplinary teams, including analysts, data scientists, or other engineers. Strong communication skills, with the ability to present ...

ingest, transform and process large and complex data sources. This can include automated web scraping and bulk data acquisition workflows. Implement data transformation, validation, and quality controls to ensure datasets are reliable, reproducible and analysis ready. Build and maintain containerised data and analytics applications (such as dashboards and data … quality Python code to work with complex or messy datasets. ( Lead Criteria) Understanding of core data engineering best practices, such as data-modelling, transformation, validation, testing, and reproducibility. Experience working collaboratively within multidisciplinary teams, including analysts, data scientists, or other engineers. Strong communication skills, with the ability to present ...