24 of 24 Model Validation Jobs in Central London

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. ...

Model Governance Director, Data Science Are you passionate about building and owning practical, scalable AI governance frameworks that enable innovation while managing risk? About the Role As Model Governance Director, Data Science, you will own and evolve the end-to-end AI and model governance framework … closely with technical, legal and product stakeholders to embed effective governance into how we use AI. Responsibilities Own the end-to-end AI and model governance framework on behalf of the Data Science function, including policy implementation and continuous improvement. Define standards for model risk classification, approvals, documentation ...

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 ...

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 ...

operate with substantial autonomy, resources, and scope in a flat, no-bureaucracy environment. Responsibilities Own the full research lifecycle, from hypothesis, experiment design, model validation, risk/overfit controls, to deployment Conduct cutting‐edge research and development in machine learning (e.g. LLMs) at scale with a focus … mastery of regression/ML for large scale data Hands‐on with modern machine learning (sequence models/transformers, representation learning, regularization, cross‐validation, causal/robust inference) applied in practice Bias to action & problem-solving demonstrated ability and comfort around owning decisions, iterating quickly, and simplifying complex problems ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

estate. Translating asset, lifecycle, application, OS, inventory, compliance and operational data into accurate dashboards and actionable insight. This role will own reporting standards, validation and stakeholder requirements to support management, risk and regulatory decision-making. What you'll do: Define data quality rules and analyse completeness, accuracy and consistency … need: Strong data analysis and reporting experience, ideally in IT Asset Management or enterprise technology operations. Expertise in data preparation, modelling, visualisation, validation and dashboard design. Ability to integrate and reconcile multiple data sources without reliance on a specific IT service-management platform. Ability to interpret complex datasets, identify ...

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 ...

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 ...