9 of 9 Remote/Hybrid Model Validation Jobs in Central London

example, Docker, FastAPI). Strong SQL, a solid grounding in relational databases, schemas and data transformations (ideally DBT), and experience preparing data for model training and scoring. Hands-on AI experience: embeddings, vector databases or RAG workflows, and NLP or sequence models applied to real-world datasets. Experience delivering ...

insights. Apply appropriate machine learning, predictive analytics and data science techniques to real-world problems. Develop and evaluate insightful models using robust performance and validation methodologies. Communicate findings and recommendations clearly to both technical and non-technical stakeholders. Contribute to development of innovative AI, machine learning and advanced analytics … analyse large-scale datasets. Develop and manage machine learning workflows within an MLOps environment. Use tooling such as MLflow, VS Code or JupyterHub for model development, experimentation and deployment. Work with technologies to access, manage and analyse data at scale (e.g., Apache Iceberg and Trino). Delivery Excellence Participate ...

regulated environments. Tomorrow’s enterprise security landscape will not look like today’s. As AI adoption accelerates, organisations face novel architectural challenges, ranging from model manipulation and prompt injection to sensitive data egress and supply chain vulnerabilities. Success requires embedding security directly into the AI development lifecycle, ensuring systems … Build & Lifecycle: Knowledge of how to integrate security controls into the AI build process (DevSecOps for AI/MLSecOps), including data pipeline security, model validation, and secure API integration. Data Protection & Egress Control: Deep awareness of data privacy challenges unique to AI, including data loss prevention (DLP), data ...

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 ...

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 ...

Strong hands-on experience with ESRI ArcGIS Enterprise, ArcGIS Pro, Portal for ArcGIS and/or ArcGIS Online. Experience in GIS data management, modelling, validation, transformation and quality assurance. Practical experience using FME (Safe Software) or equivalent ETL tools. Good knowledge of spatial data formats, GIS databases, coordinate systems ...

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 ...

Responsibilities: * Design, develop and enhance enterprise-scale risk and analytics applications. * Translate quantitative and regulatory requirements into technical solutions. * Develop & implement testing frameworks, analytical validation & data processing solutions. * Work with time-series data, risk analytics and complex financial systems. * Validate model outputs, testing results and risk factor data. … required). * Experience developing and enhancing complex enterprise applications. * Understanding of Market Risk, Capital Markets or Risk Technology. * Knowledge of quantitative analytics, data validation and testing methodologies. * Understanding of FRTB, particularly the Internal Models Approach (IMA). * Experience with time-series data processing and financial market data. Desirable: * Experience ...

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 ...