101 to 125 of 168 Model Validation Jobs in London

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 ...

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 ...

business strategy, you will bring a critical eye to how forecasts are built and how they are used. You will challenge assumptions, validate model outputs against in-market performance, and make analytical contributions that range from a single product feature to the broader picture of Teya’s economic engine. … Finance, Marketing, and Engineering to translate analytical insights into product, pricing, and commercial decisions that get implemented.• Conduct investigative analysis to identify data gaps, model limitations, and opportunities to improve valuation methodology, proactively surfacing insights that change how Teya understands its business.• Create clear, compelling presentations and documentation that ...

Systems Engineer, you'll work closely with scientists, machine learning engineers, and platform teams to design and build the systems that underpin model development and deployment. You'll contribute hands-on across data platforms, training infrastructure, evaluation systems, model lifecycle management, and production inference.More senior candidates will … large-scale multimodal datasets.Design systems that index, process, and enrich thousands of videos through machine learning pipelines.Optimize data storage and access patterns for efficient model training and experimentation.Improve reliability, scalability, and observability across the data ecosystem.ML Training InfrastructureBuild and optimize infrastructure for large-scale model training.Improve performance across ...

reporting to the Head of FP&A.You'll own two linked workstreams - IFRS9 Expected Credit Loss (ECL), and portfolio modelling that feeds the financial model to produce forecasts. The work spans the UK and US revolving credit books, sitting close to Finance, Risk and Data Science.Tech stack: Snowflake … outputs, and result checks into Snowflake.Support provisioning, impact analysis and year-end submissions with clear audit trails and documentation.Portfolio ModellingDevelop and maintain the portfolio model that feeds the financial model - active customers, balances, funding, repayments, finance charges and bad debt.Build and backtest forecasting components (spend, cashflow, cohort/ ...

term modeling vision. Who you are 5+ years' experience in credit risk modeling for consumer lending, credit cards, or BNPL. Deep proficiency in PD model development and validation, with strong knowledge of calibration techniques. Advanced Python and SQL skills; familiar with XGBoost, scikit-learn, pandas, MLFlow. Experience with … unstructured data (e.g., customer communications, credit applications). Knowledge of integrating third-party credit bureau data into production models. Understanding of champion/challenger model frameworks and A/B testing infrastructure. Exposure to loan-level economic modeling, including cost-of-capital and loss metrics. Please include ...

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 ...

prepare materials for senior risk forumsPrototype and build analytical solutions using Python and automation frameworksManage the full analytics lifecycle, including problem definition, prototyping, validation, and scalingLeverage AI-assisted tools to accelerate delivery while maintaining quality and governance standardsDevelop and validate credit loss models including probability of default, loss given … with cross-functional teamsPreferred qualifications, capabilities, and skillsExperience with solution architecture for analytical or risk platforms and familiarity with governance and control frameworks for model riskHands-on experience applying AI or machine learning methods to credit analytics and decision supportExperience working with technology teams to scale models and tools ...

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 ...

codebases where high-level technical hurdles require expert intervention. Define and drive the software V&V and test automation strategy, building infrastructure for continuous validation and championing design for testability across the engineering stack Establish compliance-as-code workflows that map verification evidence to IEC 62304 (Class … Azure) Nice to have: Experience with hardware-in-the-loop or software-in-the-loop test environments Exposure to MLOps, including model drift validation, dataset governance, and automated performance evaluation and deployment of organisational AI strategy Experience with cybersecurity requirements (e.g. IEC 81001-5-1, FDA cybersecurity guidance ...