8 of 8 Permanent Model Validation Jobs in Central London

professional services firm is expanding its AI and Data Science consulting practice, following significant team growth and increased demand for machine learning and AI model development and validation services. The Assistant Manager role will appeal to data scientists and ML engineers with a minimum of two years’ post … graduate experience who are ready to take responsibility for model development, tool-building, and technical validation across a variety of client-facing and internal projects. This opportunity offers structured career progression, exposure to a diverse range of AI use cases, and the chance to grow within a high ...

environments. Seeking Experience in most of the following: Python or similar scripting languages for data exploration and preparation. Machine learning and statistical methods, including model validation. Data analytics and visualisation techniques. Processing large datasets using batch or streaming tools such as Apache Spark. Data acquisition and fusion approaches. Cloud ...

into scalable production-grade code Collaborate closely with Front Office, Trading, Risk, and Research teams Enhance and maintain low-latency, high-performance systems Perform model validation, backtesting, and optimisation Contribute to architecture design of quant libraries and analytics platforms Ensure best practices in software engineering, testing, and documentation ...

risks within financial services sector. Proven experience leading and delivering end-to-end internal audits. Solid knowledge of AI governance and risk frameworks, including model risk management (MRM) principles, AI lifecycle controls, bias and fairness assessments, and the design and evaluation of oversight and accountability structures for AI systems. … Demonstrable experience auditing or reviewing AI and machine learning models, including model validation, explainability, performance monitoring, data quality and integrity, and the adequacy of model documentation and change management processes. Why Consultants choose the ATC Work that moves you forward When a project fits your skills ...

analysis (EDA) to uncover trends, anomalies, and opportunitie sDevelop and validate machine learning models (regression, classification, clustering, etc. )Conduct feature engineering, hypothesis testing, and model evaluatio nTranslate business requirements into data science use cases and analytical solution sDeliver actionable insights to drive optimisation, efficiency, and performance improvemen tSupport decision … driven decision-making app roachDemonstrated continuous learning mi ndset Additional Requirements (Mand atory)Hands-on experience in PythonExperience in Azure and Databricks and ML model development & Depl oymentExperience in Tableau or similar visualisation tools ...

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 ...

London Stock Exchange’s platform Real-Time Distribution System & Real-Time Managed Distribution System Transformation of the platform to a hybrid cloud model Packaging & validating multiple vendor products on our various infrastructures – cloud/on-prem (GCP/Anthos/Bare metal) Configuring & tuning market data infrastructure products ...

offs, risks, and next steps for senior stakeholders. Partner with ML and data science teams on AI-driven pricing tools: defining business requirements, validating model outputs, identifying commercial edge cases, and translating outputs into practical actions. Pressure-test pricing recommendations from a commercial perspective, considering customer impact, operational feasibility … commercial datasets. Experience working alongside ML or data science teams on AI-driven pricing or recommendation tools, including defining requirements, validating outputs, and translating model recommendations into business actions. Consulting-style problem solving: able to structure ambiguous problems quickly, work at pace, and deliver high-quality outputs for senior ...