24 of 24 Model Validation Jobs in Central London

About the Team Goldman Sachs's Model Risk Management (MRM) team plays a critical role in ensuring the safety and soundness of the firm's models. MRM validates a diverse set of models, including AI and machine learning models, used within the firm. This role offers the opportunity … significantly contributions to the firm's overall model risk management framework and AI. MODEL RISK MANAGEMENT (MRM) The Model Risk Management (MRM) group is a multidisciplinary group of quantitative experts at Goldman Sachs with presence in New York, Dallas, London, Birmingham, Warsaw, Hong Kong, and Bangalore. ...

cases across Bloomberg, including product, platform, internal tooling, automation, and third-party AI solutions. Evaluate AI risks related to bias, explainability, hallucination, robustness, model drift, data leakage, privacy, security, intellectual property, misuse, transparency, and human oversight. Advise teams on appropriate controls, testing, monitoring, documentation, and risk mitigation strategies based … case, data sensitivity, model type, deployment context, and regulatory exposure. Review complex or higher-risk AI use cases and provide risk-based recommendations to governance forums and senior stakeholders. Help define practical technical standards for responsible AI development, testing, validation, deployment, monitoring, and retirement. Framework and Control Development ...

fraud models are highly predictive and market leading - consumer bureau data, postcode insights, open source data,transactional insights & fraud indicators from partnerships Apply traditional model development techniques and approaches (e.g. logistic regression) as well as adopting new AI/ML techniques such as gradient boosting, random forests, clustering, etc. … approaches towards new fraud scores and models Consider the creation of new characteristics/attributes to improve and maximise the predictive power of the model(s) as well as enhancing and creating other analytical products and services. This can be done through expert approaches or through AI approaches (e.g. ...

commercial outcomes. You'll work across: Customer segmentation, propensity modelling and churn prediction. Revenue and demand forecasting. Python-based modelling, feature engineering and model validation. Production deployment, cloud infrastructure and MLOps. Translating complex analysis into actionable commercial insights. Collaborating with product, engineering and client teams to develop AI-powered ...

with clarity, speed, and confidence. If you are excited about this opportunity but do not meet every single requirement, 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. Skills and Competencies … Strong foundation in hydrology, hydraulics, climate science, applied mathematics, data science, computer science, or a related quantitative discipline Understanding of machine learning fundamentals including model training and validation, overfitting, and model evaluation Experience with one or more machine learning or deep learning approaches such as Long Short ...

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 ...

pricing optimisation. Apply machine learning, statistical and analytical techniques to solve complex business challenges and generate measurable business value. Evaluate and continuously improve model performance through testing, monitoring and refinement. Ensure models are scalable, reliable and suitable for operational use. Explore and analyse large and complex datasets to identify … impact of Data Science initiatives. Establish standards, frameworks and best practices for Data Science and machine learning across the organisation. Define approaches for model development, validation, deployment and lifecycle management. Develop scalable and repeatable Data Science and MLOps processes within the Azure Databricks Lakehouse environment. Collaborate with Data ...

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 our client's proprietary models supporting and coaching more junior team members Requirements Proven financial markets experience, ideally within an investment bank ...

cross-asset workflows. What's the role? We are looking for a senior product manager to run IPQA's analytics architecture and drive model delivery at scale, ensuring our analytics continue to lead as client and market needs evolve. You will work at the intersection of quantitative finance, engineering … clients across Terminal, Enterprise Data and Enterprise Products. At the core of this role is a founding conviction: analytics at scale require a model-agnostic design, where the architecture enforces consistency and transparency across models, asset classes and client workflows. You will work closely with our quant and engineering ...

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 … client site. 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 ...

encourage applications from people with diverse and underrepresented backgrounds and perspectives. Why you? 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 ...

pipelines using AWS services and experiment tracking tools Develop and integrate LLM-powered solutions for tracing, evaluation, and production monitoring Implement robust experiment tracking, model versioning, and reproducibility practices with full audit trails Design feature engineering approaches and contribute to feature store development Support production models through monitoring, performance … analysis, and continuous improvement Apply responsible AI practices, including model explainability and fairness assessment Present experiment findings and production outcomes to stakeholders, articulating operational and strategic value Mentor junior colleagues and share learnings across the team About you You will have experience in many of the following: Hands ...

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 our client's proprietary models Requirements Proficiency with C#, C++ or Python Evidence of exceptional mathematical and analytical skills Initial industry experience working ...

healthcare applications. The role sits at the intersection of clinical practice, software engineering, data science, and AI , with a strong focus on patient safety, model reliability, regulatory compliance, and real-world clinical impact. The successful candidate will work closely with clinicians, data scientists, ML engineers, software engineers, product teams … deep-learning models using appropriate clinical datasets. Develop robust data pipelines for clinical, imaging, laboratory, physiological, and/or electronic health-record data. Implement model evaluation frameworks covering performance, calibration, robustness, bias, uncertainty, and clinically relevant endpoints. Support prospective and retrospective validation of AI systems in clinical environments. ...

Moody's is expanding its Model Development team to advance inland flood catastrophe modeling that supports global risk assessment. The role involves developing, validating, and deploying advanced models, incorporating ML and AI tools, and collaborating with scientists and engineers to deliver robust, reproducible workflows. You will work with geospatial ...

clients and Bloomberg enterprise product teams to understand how firms expect to govern access — to content and to Bloomberg's capabilities — and validate the model against real firm behaviour. You'll need to have Strong product management experience in enterprise software, SaaS or platform products, leading initiatives from concept ...

Develop and evaluate statistical and machine learning models. Build segmentation, propensity, forecasting and personalisation solutions that reach real customers. Apply rigour to feature engineering, validation and model performance. Design and evaluate experiments to understand genuine impact. Work with Data Engineering to create reliable model inputs and productionise ...

Goldman Sachs in Birmingham is seeking an AI Model Risk Associate to join the Model Risk Management (MRM) team. You will validate AI models, ensure accuracy and regulatory compliance, and contribute to the firm's risk management framework. You will work with AI researchers and developers to design … validation plans, benchmark models, and apply advanced statistics and ML to manage model risk within a leading global financial institution. #J-18808-Ljbffr ...

proportionate, business-relevant advice, assurance and audit services. This role is responsible for leading and delivering specialist services in data governance, AI governance, AI model testing, and data analytics audits across Financial Services clients. As an Associate Director, you will act as a recognised subject matter expert across client … look into the role As an Associate Director within BRS, you will: Own and lead complex client engagements across data governance, AI governance, AI model testing, and analytics internal audit/risk within Financial Services, managing a significant portfolio of client relationships at senior stakeholder level. Lead strategic planning ...

An excellent opportunity for a Quantitative Analyst to join a highly talented and technically focused team based in central London. The successful candidate will be responsible for interpreting, analysing and manipulating large and complex datasets ...

between data, business capabilities, processes, applications, integrations and technology components. Develop application and technology architecture views where required to support data architecture and traceability. Model Microsoft Azure environments and services relevant to enterprise data, including data platforms, integration, storage, identity, security and networking. Assess the data and architecture implications … Maintain traceability between requirements, data, applications, technologies, integrations, work packages, deliverables and implementation milestones. Capture and structure architecture and data requirements and support their validation and traceability. Identify data, application, integration and technology dependencies, gaps, duplication, risks and inconsistencies. Assess project and solution designs against agreed enterprise architecture principles ...

Design reusable development frameworks and components, ensuring high standards across code quality, performance, testing and maintainability . Implement complex Salesforce configuration, automation, workflows, approvals, validation rules and security controls . Agentforce, AI & Data Cloud Design and develop Salesforce Agentforce and Agentic AI solutions , integrating AI-enabled capabilities into enterprise … solutions , with an understanding of how AI capabilities integrate into enterprise Salesforce processes. Strong knowledge of Salesforce architecture, administration, configuration, security models, workflow automation, validation rules and data management . Experience designing and supporting enterprise integrations using REST/SOAP APIs , alongside strong knowledge of Salesforce integration and application ...

Engineers to join the AI for Science (AI4S) team to design, implement and validate ML models for real‐world biomedical problems. You will drive model development across scientific tasks using HPC and large biomedical data sources. You will collaborate with biology, medicine and experimentation experts to ensure high‐quality … data for model development, deliver robust code in an agile environment, and contribute to state‐of‐the‐art AI/ML research and deployment. #J-18808-Ljbffr ...

signal subsystems, from block level through subsystem and top-level integration. Define the modeling approach and fidelity tiers – decide what gets a real-number model, what needs Verilog-AMS, and where transistor-level co-sim is required – and document the accuracy/runtime trade-offs. Develop and validate analog … behavioral models against transistor-level references, owning the model-vs-schematic equivalence checks that keep the abstraction honest. Build self-checking testbenches and reusable verification components for analog/digital interactions: CDR lock, adaptation and calibration loop convergence, mode and power-state transitions, clock dividers, deserializers, and clock-domain ...