51 to 75 of 168 Model Validation Jobs in London

management across Front Office, Risk, Technology, and Finance. Demonstrated ability to combine strategic thinking with practical execution. Deep experience working with Quants, Market Risk, Model Validation, and regulatory stakeholders. Robust technical grounding, with the ability to rapidly understand highly‐detailed architectures, data flows, and system integrations. Experience across ...

management across Front Office, Risk, Technology, and Finance. Demonstrated ability to combine strategic thinking with practical execution. Deep experience working with Quants, Market Risk, Model Validation, and regulatory stakeholders. Robust technical grounding, with the ability to rapidly understand highly‐detailed architectures, data flows, and system integrations. Experience across ...

stakeholder management across Front Office, Risk, Technology, and Finance.Demonstrated ability to combine strategic thinking with practical execution.Deep experience working with Quants, Market Risk, Model Validation, and regulatory stakeholders.Robust technical grounding, with the ability to rapidly understand highly-detailed architectures, data flows, and system integrations.Experience across the full SDLC ...

analytical or data science experience within credit risk or broader financial institutions, with exposure to developing predictive models. Knowledge on principles of credit risk model development, including scorecard, Basel/IRB or IFRS9 modelling (PD, EAD, LGD, etc.). UK retail lending experience. In-depth knowledge and understanding … statistical aspects (especially these which are used in Credit Risk-Basel modelling): Logistic-Linear Regression, Scorecard development model validation approaches (GINI coefficient KS- statistics) Data sampling Data mining model maintenance frameworks. Excellent analytical skills and a strong attention to detail. A qualification in a degree with relevant ...

Science teams deploy, monitor, retrain and govern models reliably at scale—from the ground up.Key Responsibilities ML Infrastructure & Deployment (40%): Build automated pipelines for model training, validation and deployment, plus model registries, feature stores and inference services, with self-serve tooling for Data Science teams.Model Monitoring & Operations … recovery for ML workloads—covering latency, data quality and drift—and own rollback, rollout and incident response.MLOps Governance & Best Practice (20%): Establish controls for model lineage, reproducibility and audit trails, and introduce ML-specific CI/CD, testing and release automation.Collaboration & Enablement (10%): Partner with Data Science, Data Engineering ...

outset.Your role operates in a high-intensity, time-critical environment and requires the ability to maintain deep experience working with Quants, Market Risk, Model Validation, Finance, and regulatory stakeholders.Responsibilities:Have responsibility for and drive end-to-end delivery of the FRTB IMA programme, with full accountability for outcomes ...

will work at the forefront of algorithmic trading, where your research and engineering directly shape market outcomes.* You can expect a hybrid working model with 3 days in the office and 2 days working remotely, giving you flexibility alongside meaningful team collaboration.* You'll thrive in a collaborative, performance ...

offerYou will work at the forefront of algorithmic trading, where your research and engineering directly shape market outcomes.You can expect a hybrid working model with 3 days in the office and 2 days working remotely, giving you flexibility alongside meaningful team collaboration.You'll thrive in a collaborative, performance-driven ...

providing excellent service to internal and external customersPartner with Product, Application Specialists, and Sales to thoroughly understand our client’s workflows to further our model engine, improve our product offering, and provide client support for advanced risk analytics and valuationsResearch industry standards, trends, and best practices on financial analytical ...

software systems, not just declarative pipelines or SQL-only workflows Proficiency in Go or Python (or similar general-purpose language) Experience with data modeling, validation, and transforming real-world data into usable formats BS in Computer Science, Engineering or Bioinformatics, or a related field, or equivalent practical experience Preferred ...

deep-learning framework (TensorFlow/PyTorch).You possess a solid grasp of core data science techniques (supervised/unsupervised learning, time-series, NLP, model validation) and the ability to innovate new algorithms.You apply a rigorous scientific and entrepreneurial mindset, translating complex business problems into a mathematical framework … measuring model impact upon deployment.You are an exceptional communicator, adept at translating complex technical solutions into persuasive, actionable insights for senior and non-technical audiences.You contribute to team success by project planning, assessing technical feasibility, estimating delivery timelines, and achieving measurable outcomes.Our Interview ProcessTalent Team Screen (30 minutes)Take ...

ready insights grounded in trusted data and established metrics. About the role: We are seeking a Data Scientist III to help the design and validation of Agentic AI-driven product capabilities within Protégé in PatentSight. This role focuses on defining what to build and why, leveraging machine learning … including hybrid search (semantic + lexical), and evaluation metrics (e.g., relevance, ranking quality). Analyse large-scale IP datasets to extract insights and improve model performance. Establish best practices for model evaluation, validation, and benchmarking. Translate experimental results into clear product recommendations and business impact. Collaborate with ...

JPMorgan Chase & Co. is seeking a Quant Modeling Associate/Vice President in their Model Risk Governance and Review team. This role involves assessing and mitigating model risk for electronic trading models while providing exposure to a range of business areas. Ideal candidates will hold a Master … quantitative field and possess strong experience in model validation and electronic trading. The position requires excellent communication skills and proficiency in Python. #J-18808-Ljbffr ...

analytics, and integration layers. This role is critical to enabling the organisation to move from fragmented, siloed data to a coherent, governed enterprise data model that powers scalable growth. This is a full-time position for an initial 3-month contract, for a Q3 start date. Responsibilities Define, evolve … firm's core buy-side data domains: positions, valuations, transactions, orders, client/AUM data, reference data, ESG/RI data, and benchmarks. Model the investment lifecycle end-to-end: order generation, execution, allocation, settlement, corporate actions, performance attribution, and accounting impacts (IBOR/ABOR). Establish clear semantics ...

integrity, transformations, and large datasets across complex environments. Hands-on expertise with Azure Data Factory (ADF) and Azure DevOps, including ETL workflow testing, pipeline validation, test management, and defect tracking. Advanced SQL skills with the ability to write queries, interrogate databases, read schemas and tables, and perform data reconciliation ...

integrity, transformations, and large datasets across complex environments. Hands-on expertise with Azure Data Factory (ADF) and Azure DevOps, including ETL workflow testing, pipeline validation, test management, and defect tracking. Advanced SQL skills with the ability to write queries, interrogate databases, read schemas and tables, and perform data reconciliation ...

integrations, serving as a reliable liaison who can translate between technical and business contexts• Support change management activities for new system implementations, including testing, validation, and documentation of updated processes• Contribute to process improvement initiatives identifying inefficiencies in existing workflows and proposing practical, scalable solutionsBasic qualifications- Bachelor's degree ...

least 5 years of experience as a Business Analyst in Quant Risk Functional/Technical Competencies: THE BANK counterparty credit risk uses an advanced model for PFE so the BA needs to be quantitative and familiar with these advanced tools. THE BANK use a vendor based calculation engine ...

emerging area, so part of the role will be to shape the problem space by working with other teams to find, validate and model useful signals for participant quality. The ideal candidate will help define the right problems to solve, not just execute against a fixed brief. The Applied ...

internal initiatives.Support clients in navigating emerging AI regulations, standards, and guidance while enabling innovation and business value.Facilitate workshops, governance forums, risk assessments, and operating model design activities with senior stakeholders.Live in-person whiteboarding sessions to problem solve as a team, alongside asynchronous communication on Teams.Hybrid working with the team … Values | PA Consulting.QualificationsEssential requirements You must be an established consulting professional with experience delivering projects focused on AI governance, responsible AI, AI risk management, model governance, or emerging technology regulation within the private sector. Ideally, you should have experience consulting with Life Sciences, Government or Consumer & Manufacturing sector clients.Even ...

TeamJoin our Financial Risk Management (FRM) team, where we develop, validate, and enhance the methodologies that underpin Swiss Re's financial risk framework.Our Financial Model Validation & Methodologies team, based in London, Zurich, and Bangalore, works at the intersection of risk management, actuarial science, finance, and technology to strengthen … risk capture methodologies.Enhance risk systems to reflect evolving portfolio characteristics, market dynamics, and regulatory requirements.Contribute to the integrity of Swiss Re's Internal Capital Model, ensuring methodologies remain robust, transparent, and fit for purpose.Serve as a subject matter expert on market and credit risk methodologies, providing advice and insight ...

technical hardware-and-software architect role, not a strategy-only position. The successful candidate operates comfortably across GPU infrastructure, high-performance networking, model training and inference pipelines, and the AI risk/governance disciplines increasingly demanded by regulators and enterprise boards.The Enterprise Architect will lead technical delivery teams … frameworks, inference/serving platforms, MLOps/LLMOps tooling, vector databases, and retrieval-augmented generation (RAG) and agentic architectures.Define and AI governance frameworks covering model risk management, responsible AI, data lineage, bias/fairness testing, explainability, and regulatory alignment (EU AI Act, NIST AI RMF, ISO/ ...

Financial Risk Management (FRM) team, where we develop, validate, and enhance the methodologies that underpin Swiss Re's financial risk framework. Our Financial Model Validation & Methodologies team, based in London, Zurich, and Bangalore, works at the intersection of risk management, actuarial science, finance, and technology to strengthen Swiss … methodologies. Enhance risk systems to reflect evolving portfolio characteristics, market dynamics, and regulatory requirements. Contribute to the integrity of Swiss Re's Internal Capital Model, ensuring methodologies remain robust, transparent, and fit for purpose. Serve as a subject matter expert on market and credit risk methodologies, providing advice ...

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 ...

output into understandable and actionable business knowledge.Manage dataset creation including data extraction, derived and dependent variable creation, and data quality control processes for analytics, model development, and validation. Monitor execution of analytical solutions, including criteria specification, data sourcing, segmentation, analytics, selection, delivery, and back-end data capture results.Contribute … application of analytic output.Embed analytic programs and tools. Ensure continued accuracy, relevancy, and effectiveness and track process improvements once deployed.Ensure adherence to data and model governance standards that are set and enforced by industry standards and/or enterprise business unit data governance polices and leaders.May lead or provide ...