16 of 16 Permanent Model Validation Jobs in London

make an impact. Job Responsibilities Develop mathematical models for the valuation of credit derivatives, structured lending facilities, and illiquid collateral Implement methodologies for model calibration and build analytics to manage model risk appetite Leverage machine learning, AI, and data analytics to enhance valuation methodologies and drive innovation Define … methodology for pricing adjustments, model limitations, parameter uncertainty, and liquidity reserves Monitor model performance metrics to ensure models behave as expected over time Design and develop software frameworks for analytics delivery to systems and applications Collaborate with front office trading desks, controllers, and model risk teams ...

team performance. Manage the full modelling lifecycle , ensuring best practices in data science, statistical rigour and engineering are applied from data collection through to model validation, automation and delivery to the end users. Undertake research projects that address critical football questions, delivering novel insights that shape club strategy … data science, statistical modelling, and machine learning techniques. Expert understanding of statistical programming languages , especially Python and/or R, for data analysis and model development. Proficient in SQL development and knowledgeable about database and data warehousing technologies. Experienced with cloud-based computing environments, ideally GCP, demonstrating proficiency ...

design and architecture of actuarial, reinsurance and valuation solutions across the remit of M&P function. This role ensures that all model and system changes are designed holistically across methodology, models, systems, data, processes and reporting, delivering solutions that are robust, scalable, efficient and aligned with both business strategy … guidance during implementation to ensure design intent is realized 4. Architecture & Standards • Define and maintain actuarial architecture principles and standards. Drive consistency across: o Model design o Data structures and flows o System integrations o Reporting frameworks • Promote best practices in automation, modular design and scalability 5. Governance, Risk ...

design principles, including accessible colour selection and charting best practices. Benefits Full benefits package, including travel perks, generous time‐off, parental leave, flexible work model, and career development resources. Equal Employment Opportunity Expedia Group is committed to creating an inclusive work environment with a diverse workforce. All qualified applicants ...

structured ML outputs with LLM-based reasoning to deliver explainable scores Work closely with stakeholders to translate credit policy into data-driven workflows Support model validation, explainability, and performance evaluation Requirements Strong experience as a Senior Quant Data Scientist Deep understanding of: Regression, classification, and ranking models Time ...

deliver measurable business impact. Design and enhance margin and derivative models, including methodology selection, calibration, numerical schemes, benchmarking/backtesting, documentation, and alignment with model risk governance. Serve as model owner: manage roadmaps, controls, monitoring/alerts, change management, and responses to Model Risk, Audit, and regulatory … reviews; ensure explainability and transparency of assumptions, limitations, and model performance. Build and productionize analytics that advance intraday/EoD automation (services, APIs, pipelines) with clear SLOs/SLA, observability, reliability engineering practices, and tight integration into trading/risk platforms. Provide technical leadership and mentorship; conduct code/ ...

timing risk, and other key cost drivers. Leverage AI and machine learning tools across the development lifecycle, from accelerating research and prototyping to enhancing model validation, code review, and continuous performance monitoring in production. Develop and maintain client‐specific algorithm customizations, respond to BAU and analytics requests … execution impact. Build and back‐test models on tick‐level and order‐level data; translate findings into production components with measurable performance improvements. Model internal and external liquidity sources to optimize algo interaction across the full liquidity landscape. Production Engineering & Delivery Write clean, efficient, production‐quality code where latency ...

deliver measurable business impact. Design and enhance margin and derivative models, including methodology selection, calibration, numerical schemes, benchmarking/backtesting, documentation, and alignment with model risk governance. Serve as model owner: manage roadmaps, controls, monitoring/alerts, change management, and responses to Model Risk, Audit, and regulatory … reviews; ensure explainability and transparency of assumptions, limitations, and model performance. Build and productionize analytics that advance intraday/EoD automation (services, APIs, pipelines) with clear SLOs/SLA, observability, reliability engineering practices, and tight integration into trading/risk platforms. Provide technical leadership and mentorship; conduct code/ ...

with production stability. Engineering & AI Execution Lead cross‐functional teams across engineering, data science, and ML engineering. Establish best practices for AI development, including model validation, monitoring, and retraining. Drive adoption of modern engineering standards (CI/CD, DevOps, automated testing). Ensure seamless collaboration between data, product … regulations and AI governance standards. Establish frameworks for ethical AI use, explainability, and bias mitigation. Partner with Legal and Compliance on data usage and model accountability. Maintain robust security practices across data and infrastructure layers. Leadership & Collaboration Build and scale high‐performing teams in engineering, AI, and data. ...

strongly encourage applications from people with diverse and underrepresented backgrounds and perspectives. Responsibilities 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 ...

language for the large-scale analysis and production of securities data Research and development of market dynamics across multiple asset classes Prototyping, testing, and validation of TradingHub’s proprietary models supporting and coaching more junior team members Requirements Proven financial markets experience, ideally within an investment bank or pricing ...

define success metrics, guardrails, and decision frameworks, translating analytical results into actionable product and operational actions. Define and uphold engineering standards and guidelines for model development, including validation, uncertainty, reproducibility, and bias/quality checks. Drive scalable experimentation with A/B and Multi-armed bandit testing frameworks … variance reduction, and online-offline alignment. Work together with Data Engineering, MLOps, and Game Tech teams to guarantee dependable data foundations, feature accessibility, and model deployment pathways. Build internal data products to improve the speed and quality of decision-making, such as AB-test calculators, decision tools, and automated ...

data science project lifecycle: develop, deploy, monitor, and scale models through the full Software Development Life Cycle, perform exploratory data analysis, proof‐of‐concepts, model benchmarking, and validation experiments for both ML and GenAI approaches, partner with business leaders, domain experts, and end‐users to gather requirements ...

Senior Quantitative Developer/Research & Data Engineer Research & Data Engineer UNITED KINGDOM Senior Quantitative Developer/Research & Data Engineer - LONDON - UNITED KINGDOM Primary Skills - Python, C++, quantitative, research, market data, simulation frameworks Secondary Skills - distributed ...

capture, analyse, document, and prioritise business requirements and functional specifications across Legal, Compliance, Technology, and Operations. Contribute to future‐state business architecture and operating model design to support new and existing Blockchain/DLT use cases. Collaborate with cybersecurity, risk, and controls teams to implement governance and regulatory requirements … evidence needed for approvals. Drive documentation and delivery of end‐to‐end business workflows for tokenisation and on‐chain settlement models, coordinating testing/validation and launch readiness across teams. Monitor internal and external blockchain/DLT capabilities and vendors; synthesise options and trade‐offs (feasibility, maturity, cost, time ...

mathematical models and pricing papers in detail. The candidate should be capable of verifying pricing numbers against market standards and supporting client-facing validation documentation. Strong Java experience is required because the team works primarily in a Java-based environment. Specifically need someone who understands both quantitative modelling … high-performance engineering. Requires strong experience in performance optimization, scalable pricing implementations, and low-latency quantitative systems. Many quants focus only on model correctness and ignore performance considerations, whereas this role requires both numerical accuracy and production efficiency. Candidates from organizations or platforms such as Murex, Calypso, Numerix ...