1 to 25 of 45 Model Validation Jobs in England

growth of communities and economies globally for more than 300 years.Through a comprehensive suite of trusted financial market infrastructure services – and our open-access model – we provide the flexibility, stability and trust that enable our customers to pursue their ambitions with confidence and clarity.LSEG is headquartered in the United … LSEG is a place where everyone can grow, develop and fulfil your potential with meaningful careers.**Role Purpose:**We are seeking an experienced **AI & Model Evaluation Manager** to lead the evaluation, validation, and governance of advanced AI, machine learning, and statistical models across our Active Data Layer programme ...

dependencies, and constraints. * Reviewing design artefacts, integration plans, and testing strategies to provide assurance across workstreams. * Ensuring AI components adhere to SDLC updates, including model validation, safety checks, and governance protocols. * Engaging with external AI technology providers to clarify technical requirements and integration considerations. * Supporting engineering teams … resolving complex technical challenges related to AI model behaviour, data flows, and system interfaces. * Coaching developers and data engineers to maintain quality and consistency. What you'll bring: * Proven experience leading engineering teams in AI or related fields. * Strong understanding of AI components such as LLMs, AI logic ...

growth of the project pipeline. Leading the design, development and deployment of AI and machine learning solutions. Advising clients on AI governance, model risk, validation and responsible AI practices. Collaborating with technical and non-technical stakeholders to translate business challenges into scalable AI solutions. Coaching and mentoring junior … delivery experience across data science, analytics and machine learning projects. Strong understanding of AI and machine learning modelling techniques. Experience with AI governance, model validation and responsible AI frameworks. Experience coaching and mentoring technical teams. Strong coding standards and software engineering best practices, including testing and code reviews. ...

science, setting best practices and standards across the organization Mentor and guide junior and senior data scientists, fostering a high-performance, collaborative team environment Model Development & Deployment Develop and deploy machine learning models for use cases such as: Fraud detection Credit risk modeling Customer segmentation and personalization Forecasting … adoption Data Strategy & Governance Support the development of data strategy frameworks, ensuring alignment with regulatory and compliance requirements Promote best practices in data governance, model validation, and ethical AI usage Qualifications: Required Background: MSc or Higher in Artificial Intelligence, Computer Science, Data Science, or a closely related discipline ...

days) The Opportunity There are very few roles in the UK market where you can take ownership of a proven, production-grade credit risk model that is already outperforming competitors - and be given the autonomy to evolve it, refine it and directly influence commercial outcomes. This … embedded at the core of how the business makes decisions. At the centre of this capability is a highly accurate credit risk model, supported by rich, real-world datasets and a continuous feedback loop of internal and external lending outcomes. The model is already delivering strong predictive performance ...

deploy machine learning models into production environments. You will work closely with data scientists and software engineers to develop scalable ML pipelines, optimise model performance, and integrate machine learning capabilities into production systems. The role involves working with large datasets, building robust ML systems, and supporting the full lifecycle … Collaborate with data scientists to transition models from research to scalable production systems ML Engineering and Deployment • Design and maintain machine learning pipelines and model deployment infrastructure • Implement automated model training, validation, and monitoring processes • Ensure models are scalable, reliable, and performant in production environments Data Engineering ...

risk and valuation frameworks and industry best practices Lead project teams, mentor and supervise junior team members, ensure high-quality deliveries and adhere to model governance upmost standards Support content generation and business development initiatives, including identifying new opportunities and developing proposals Your competences Technical: Post-graduate degree … maths from a top tier university Minimum of 8-12 years of relevant experience in quantitative modelling and derivatives pricing across Front Office, Model validation or Risk functions within financial services Solid background in stochastic calculus and data science including AI/ML techniques Experience with flow ...

ensure our tools and platforms remain cutting‐edge. Champion AI tools and solutions through AI governance committees for approval, demonstrating compliance with security standards, model validation requirements, and regulatory guidelines to ensure safe release into production. Monitor and maintain compliance of deployed AI tools through regular security audits ...

opportunities Apply statistical and machine learning techniques to address business questions Use segmentation and clustering techniques where appropriate to support insight generation Interpret model results and communicate insights clearly to technical and non-technical audiences Support model validation, documentation, and ongoing monitoring Contribute to continuous improvement ...

lending portfolios. Act as functional owner of valuation logic and assumptions. Validate, reconcile, and explain valuation outcomes end‐to‐end. Lead impact analysis for model, portfolio, or policy changes. Support SOx, audit, and model validation discussions. Provide functional direction to data scientists and engineers. Drive knowledge transfer … implementable calculation rules. Proven ability to validate and explain valuation outcomes. Strong understanding of data inputs and calculation chains. Experience leading impact analysis for model/policy changes. Supports compliance, audit, and validation processes. Degree educated or equivalent experience. Nice to Have: Strong communication skills for collaboration across ...

ensure our tools and platforms remain cutting-edge. Champion AI tools and solutions through AI governance committees for approval, demonstrating compliance with security standards, model validation requirements, and regulatory guidelines to ensure safe release into production. Monitor and maintain compliance of deployed AI tools through regular security audits ...

analytical background with curiosity to explore data beyond the initial brief. What They Offer Salary up to £65,000 depending on experience. Hybrid working model with two days per week in London and flexibility for Northern based candidates. Exposure to a wide range of industries and business problems. Clear ...

models Strong Python + SQL (R also useful) for analysis, modelling, and repeatable data workflows Good grounding in actuarial principles (rating, loss cost, segmentation, validation) Experience with claims analysis and linking claims/risk insights back to pricing actions Comfortable working cross-functionally in a fast-moving environment Able ...

models Strong Python + SQL (R also useful) for analysis, modelling, and repeatable data workflows Good grounding in actuarial principles (rating, loss cost, segmentation, validation) Experience with claims analysis and linking claims/risk insights back to pricing actions Comfortable working cross-functionally in a fast-moving environment Able ...

phase of a pricing programme due to launch in July. Key Responsibilities Support the execution of pricing initiatives and projects Analyse and validate pricing model outputs and their business impact Monitor and assess performance of pricing experiments and tests Deliver day-to-day operational analysis and reporting Partner with ...

central planning stakeholders. This role will focus on maintaining momentum, validating existing models, and supporting day-to-day pricing and performance analysis. While model building is a bonus, the priority is ensuring current processes are understood, documented, and effectively utilised. Key responsibilities include: Validating and sense-checking existing pricing ...

integration of sensors, actuators, and refrigeration hardware into complete systems. Collaborate with cross-functional teams to define system architecture and technical requirements. Support testing, validation, and continuous improvement activities throughout development. Prepare and maintain technical documentation including specifications, control logic, and operating procedures. Experience Required Ideally have a degree ...

Engineering Assurance Provide assurance across AI engineering workstreams Review design artefacts, integration plans and testing approaches Ensure AI components align with SDLC updates, including model validation, safety checks and governance controls Problem Solving & Enablement Support engineering teams in resolving complex technical challenges related to AI model behaviour ...

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 ...

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 ...

deploy scalable data solutions within AWS environments (e.g. S3, Glue, Lambda, Redshift, or equivalent services) Develop dashboards and data visualisations to translate complex model outputs into clear, actionable insights for stakeholders Support backend development where required, particularly around data APIs, pipelines, and integration layers Collaborate with data engineers, analysts … business stakeholders to define requirements and deliver end-to-end solutions Ensure model performance, validation, monitoring, and continuous improvement Contribute to best practices across data science, engineering, and cloud-based data architecture Key Skills & Experience Essential Strong experience in Bayesian statistical modelling and hierarchical modelling techniques Proficiency ...

business, to create exciting data and modelling technology agenda. The individual will be a self-starter and possess a drive for results.pladis organization model is based on 8 regions with full accountability of their own P&L* Global* UK & Ireland* Europe & Emerging Markets (EEM)* Türkiye, Central Asia (TURCA)* Middle …/ML tools in areas such as product and process prediction with primary focus in Cocoa and Chocolate.* Guide teams on appropriate model governance, validation, and robustness.* Design experiments (DoE) and multivariate studies to generate high‐value datasets for modelling and scientific discovery.* Build hybrid mechanistic + data ...

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 ...

robust data pipelines and feature-engineering workflows across large industrial datasets. Apply signal processing and machine learning techniques to operational data. Implement and optimise model inference pipelines. Develop and maintain containerised ML workloads using Docker and cloud-native tooling. Collaborate cross-functionally with engineering, analytics, and domain experts. Contribute …/CD automation, testing frameworks, code reviews, and software engineering best practices. Support end-to-end MLOps processes including deployment, monitoring and model validation. Explore and implement generative AI capabilities including LLMs, RAG pipelines, and intelligent workflow automation. Key Skills: Commercial experience in Machine Learning Engineering, Applied ...

government or regulated environments Strong hands-on experience with Python for data science and machine learning Solid understanding of machine-learning techniques (supervised, unsupervised, model evaluation) Experience with MLOps practices, including: Model versioning and deployment CI/CD for ML workflows Monitoring and performance management Experience working with … stakeholders Responsibilities Design, build, and evaluate machine-learning models to solve real-world government problems Use Python and related libraries to explore, transform, and model complex datasets Work with engineers to integrate models into production pipelines using MLOps best practices Validate, test, and monitor models to ensure accuracy, reliability ...