12 of 12 Model Validation Jobs in London

artefact handling, versioning of data/models/code Implement observability for ML systems: monitoring, alerting, logging, dashboards, and incident response for data + model health Establish best practices for data quality and ML quality: validation checks, pipeline tests, lineage, documentation, and SLAs/SLOs Optimise cost … strong DE foundations) shipping production pipelines Strong Python and SQL skills; ability to write maintainable, testable, production-grade code Solid understanding of MLOps fundamentals: model lifecycle, reproducibility, deployment patterns, and monitoring needs Hands-on experience with orchestration and distributed processing in a cloud environment Experience with data modelling ...

Build scalable data workflows and feature stores for ML applications. Infrastructure & tooling: Containerise applications with Docker, orchestrate with Kubernetes, and deploy securely in AWS. Model governance: Apply best practices for evaluation, drift monitoring, and compliance. Collaboration: Partner with Data Scientists and business stakeholders to translate insights into production-ready ...

engineers to design, experiment, validate, and deploy production-grade AI systems for customer-facing applications. Key Responsibilities Lead hypothesis generation, experimentation, and model validation to support new AI/ML business solutions. Design, run, and manage data science experiments with high standards of rigor and reproducibility. Build … Familiarity with LLM fine-tuning, evaluation frameworks, or prompt engineering. Contract Details Location: London or Edinburgh Duration: 3-month initial contract Start: ASAP Working model: Hybrid Guidant, Carbon60, Lorien & SRG - The Impellam Group Portfolio are acting as an Employment Business in relation to this vacancy. ...

Work closely with the product team to prioritise features, refine user stories, and support the full product lifecycle. Assist in functional design, testing, and validation of new features before release. Help maintain internal product documentation, user workflows, and configuration standards. Pre-Sales & Demo Environment Configuration Configure and maintain ...

environment. The Data Scientist role suits a hands-on Data Scientist who is comfortable working across the full lifecycle from data exploration through to model development validation plus deployment support. Responsibilities for the Data Scientist: Develop statistical models machine learning solutions analytical frameworks to address complex business problems … outputs into clear insights recommendations for technical non-technical stakeholders Work closely with data engineers analysts to ensure models are production-ready scalable Validate model performance manage bias ensure outputs are robust explainable reliable Contribute to continuous improvement of data science practices tooling governance Essential Skills for the Data ...

executive reporting; escalate early with clear options and impacts. Ensure comprehensive risk & control coverage: operational risk, conduct risk, data privacy, regulatory obligations, and model/process validation. Coordinate front-to-back stakeholders (Product, Sales, Operations, Finance, Risk, Compliance, Legal, Regulatory Change) to shape solutions. Drive continuous improvement and process ...

graduate) who is passionate about responsible AI, agentic systems, and the science behind guardrail effectiveness. This role sits at the intersection of research, model development, and deep validation , contributing to safety frameworks that directly shape the bank's AI strategy. The client is advancing its next generation … voice, and even emerging multimodal systems. This role is based in Edinburgh OR London. This role will be Via Umbrella. Working in a Hybrid Model of 2 days a week on site. What You'll Do As an AI Research Engineer, you will be focused on designing and building ...

agentic AI – across research, rankings, submissions and product innovation. Oversee the end-to-end analytics lifecycle, from data acquisition and feature engineering through to model development, validation, deployment and monitoring Ensure AI-driven outputs are explainable, transparent and aligned with Chambers’ standards and reputation for independence Provide strategic … outcomes Collaborate with Product and Technology teams to embed AI and analytics into customer-facing products and internal platforms Establish best practices for experimentation, model governance, performance measurement and ethical AI use Define and oversee evaluation frameworks for LLM and GenAI outputs, ensuring accuracy, consistency, bias mitigation and alignment ...

large‐scale codebase modernisation, and collaboration with Quant, Product, and Engineering teams. You will work on refactoring legacy C++ analytics libraries, improving performance, enhancing model accuracy, and supporting the transition to a modern Azure‐based architecture. This role is ideal for engineers who thrive in complex problem‐solving environments … Cloud & Platform Modernisation · Support the migration of analytics components to Azure cloud services. · Collaborate with platform engineers to ensure seamless deployment and integration. Data & Model Integrity · Validate analytics outputs, pricing models, and risk calculations. · Work closely with Quant teams to ensure model consistency and correctness. Engineering Excellence · Apply ...

models that learn across multiple data modalities and scales, from granular signals through to population-level insights Embeds explainability, uncertainty and causal reasoning into model design, not as an afterthought Partners closely with downstream teams to ensure models can be fine-tuned, deployed and deliver real-world impact Makes … clear, defensible build vs adapt vs buy decisions across models, tooling and external partnerships Sets standards for model evaluation, bench-marking, validation and data quality Represents the organisation externally through publications, open-source contribution or recognised thought leadership What success looks like Reusable AI systems that are actively ...

Data Capture (CDC) pipelines, ensuring accurate, low-risk data movement with zero-surprise cutovers. The role involves deep involvement across data modelling, integration architecture, validation, reconciliation, and event-driven design. Key Responsibilities Design and operate CDC pipelines (IBM CDC, Precisely or equivalent) Migrate data from Db2/mainframe … Deliver dual-run migrations, cutover planning, rollback and reconciliation Perform logical and physical data modelling (OLTP and analytics trade-offs) Ensure strong data quality, validation and governance controls Essential Skills Proven experience as a Data Architect or Data Migration Architect Strong Db2 and mainframe (z/OS) knowledge Hands ...

Company Akkodis is a global leader in engineering, technology, and R&D, harnessing the power of connected data to drive digital transformation and innovation for a smarter, more sustainable future. As part of the Adecco ...