151 to 175 of 328 Model Validation Jobs in England

Job Requirements At Siemens Healthineers, we pioneer breakthroughs in healthcare. For everyone. Everywhere. Sustainably. We are looking for a Finance Data Scientist to join our Magnetic Resonance business and help us turn complex financial and ...

About CyberCube: CyberCube delivers the world's leading analytics to quantify digital risk , helping the largest global carriers, reinsurers and brokers understand, price and manage cyber risk in financial terms. AI at our foundation, cyber ...

Atmospheric AI Limited in London is seeking a strong modelling specialist to build physics-based transformation and conversion models for materials economics and carbon accounting. You will enforce mass and energy balances and validate models ...

reliability. Write, review, and improve high‐quality production code while promoting engineering best practices. Provide constructive technical guidance and code review feedback, including validation of AI‐generated code. Champion software engineering excellence through testing, automation, documentation, and continuous improvement. AI‐Native Software Development Build production‐grade AI agents … solve real‐world business challenges. Required experience developing evaluation and testing frameworks for LLM and AI‐agent solutions, including regression testing, evaluation datasets, and model performance validation. Experience leveraging AI‐assisted development practices and transforming manual engineering workflows into automated solutions. Experience with infrastructure as code, CI/ ...

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 ...

real-time development for the F1 ECU, validating code with SIL/HIL/DIL, data analysis, and contributing to DevOps tooling and plant-model validation in a high-performance motorsport environment. #J-18808-Ljbffr ...

Options Modelling Team. You will develop, validate and maintain quantitative models for FX options risk, primarily using C++. You will manage model risk, produce analytics for risk management, and communicate complex results to stakeholders including senior leadership. The role requires deep quantitative skills, experience with FX and interest rate ...

complex dynamic systems within the Actuation Systems Centre of Excellence Servo domain. The role combines technical leadership with hands-on modelling and hardware validation, on a hybrid pattern requiring 2-3 days per week on-site. Applicants should hold an appropriate technical degree and have strong Matlab/Simulink ...

investigate, compare and optimise new architectures Develop signal processing algorithms and evaluate their impact on link performance Use MATLAB, Python or C++ to model communication systems and test new ideas Work with architects and IC designers to translate research concepts into practical transceiver architectures Analyse system limitations including signal ...

complex engineering environments where safety, reliability, and technical rigour are essential. What you will do: Lead and contribute to the design, modelling, verification, and validation of control and protection functions Build and use simulation models to assess system behaviour and performance Review technical solutions, identify risks, and propose safe ...

device-centric API, engineers can use devices for purposes such as low-level hardware bring-up using custom firmware and kernels, validating ML model performance on released hardware, all the way to automating the UI with XCTest to validate Apple’s cloud services.Join us to solve problems spanning maintaining ...

governance and engineering assurance. Provide leadership on systems integration, technical risk, safety assurance and cyber security considerations. Apply systems engineering principles, including the V-model, verification and validation. Work closely with project management, clients, end users and specialist engineering teams to resolve technical challenges. Ensure engineering solutions meet contractual ...

control strategies, and failure responses Perform trade studies to support architecture and design decisions Validate and maintain engineering models throughout the development lifecycle Verification & Validation Generate test specifications, procedures, and acceptance criteria Support laboratory, rig, subsystem, and system-level testing activities What You'll Bring To help us make ...

with stakeholders, pick the right approach (which may not always be ML), and set clear success metrics tied to commercial outcomes Own the full model lifecycle: scoping, development, validation, deployment, monitoring, scheduled recalibration and retirement ML Ops and production Set up ML Ops standards: version control, model … stack (GCP, Snowflake, Airflow), with reliable scoring pipelines and outputs that downstream tools and teams can use Build monitoring and observability for model accuracy in production (tracked against agreed thresholds and baselines), data drift and business impact, with clear alerts and review cycles Advanced analytics and measurement ...

engagements: maturity assessments, AI risk appetite, taxonomy and policy, operating models (roles across the three lines, forums, decision rights, escalation), integration with enterprise risk, model risk, data, cyber and privacy, and ISO/IEC 42001 readiness. Run AI estate discovery (including shadow AI), use-case classification and risk tiering … view, ending in a prioritised roadmap. Assess AI risk at use-case level, inherent and residual, covering customer and conduct harm, data and privacy, model and output, security and operational risk, across machine learning, generative AI and agentic AI. Design proportionate controls and guardrails, human oversight and approval workflows ...

domains. Design, implement, and evaluate AI models incorporating text, image, and multimodal reasoning capabilities. Develop and optimise Retrieval-Augmented Generation (RAG) architectures. Drive experimentation, model evaluation, benchmarking, and validation activities. Fine-tune and adapt foundation models for business-specific use cases. Collaborate with engineering teams to transition research … Mistral, or equivalent. Experience with Vision Language Models (VLMs) including CLIP, BLIP, and related multimodal architectures. Strong understanding of prompt engineering, fine-tuning, and model optimisation. Experience designing and implementing RAG pipelines. Deep knowledge of multimodal AI, vision-language fusion, and reasoning systems. Experience evaluating model performance, robustness ...

used by institutional clients. As an early member of a small, senior team, you will work end‐to‐end across research, prototyping, data engineering, model implementation, production systems, and client‐facing applications. This is a high‐ownership role for someone who is comfortable contributing wherever needed in a fast … empirical methods, and the application of these concepts in the investment industry. Familiarity with cloud infrastructure, containerisation, orchestration, and CI/CD for model deployment. Experience in building institutional‐grade analytical tools or dashboards for sophisticated end users. Prior experience in a startup or early‐stage technology environment. Compensation ...

support decision taking and design laboratory, glasshouse and field trials. Guiding technical managers in designing field trials aimed at validating scientific hypotheses and model predictions. Working with R&D IT and software developers to improve data-models integrations and to deploy applications tailored on shareholders’ needs. Monitoring and exploring … experience in developing machine-learning models relevant to biological or crop protection outcomes. Hands-on experience leveraging generative AI (genAI) approaches for data exploration, model development, or research acceleration is a plus. Knowledge of data analysis and extracting data insights and new understanding, while communicating scientific and data concepts ...

responds to it. We decode risk to unlock opportunity, helping our clients navigate uncertainty with clarity, speed, and confidence. 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 … OpenAI Agents SDK, with an understanding of agent design patterns including tool use, orchestration, memory, and multi-agent workflows Ability to own the full model-development lifecycle, including problem framing, data exploration, solution design, estimation, validation, deployment, and ongoing monitoring Ability to explain, present, and demonstrate complex modeling ...

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 ...

financial markets and asset management line of business Strong business domain knowledge in ESG, investment stewardship, or buyside investment Familiarity with techniques for model explainability and self-validation CFA or equivalent financial qualification #J-18808-Ljbffr ...

Data Analytics. Advanced Power BI dashboard development and data visualisation. Experience with AI-enabled conversational insights. Exploratory Data Analysis (EDA) and feature engineering. Model development, selection and validation. Model governance, productionisation and monitoring. Experience managing the full end-to-end data science lifecycle. Ability to translate complex analysis ...

analyses of optical modes, resonance and beam profiles, and drive epi design decisions. The role requires deep knowledge of laser physics, device modelling and validation against experimental data, with a focus on high-speed, energy-efficient light sources for interconnect applications. #J-18808-Ljbffr ...

term modeling vision. Who you are 5+ years' experience in credit risk modeling for consumer lending, credit cards, or BNPL. Deep proficiency in PD model development and validation, with strong knowledge of calibration techniques. Advanced Python and SQL skills; familiar with XGBoost, scikit-learn, pandas, MLFlow. Experience with … unstructured data (e.g., customer communications, credit applications). Knowledge of integrating third-party credit bureau data into production models. Understanding of champion/challenger model frameworks and A/B testing infrastructure. Exposure to loan-level economic modeling, including cost-of-capital and loss metrics. Curious to learn more ...

financial services business. The role will focus on developing and delivering data science solutions across the full machine learning lifecycle, from data preparation and model development through to deployment and monitoring. Working closely with technical teams and commercial stakeholders, the successful candidate will use data science to solve business … Previous production experience is not essential, as training and development will be provided. Key Responsibilities Deliver data science projects covering data preparation, exploratory analysis, model development and validation. Contribute to the deployment and ongoing monitoring of machine learning models. Take increasing ownership of the full model lifecycle. Apply ...