1 to 25 of 38 Model Validation Jobs in the South East

everyone. We employ more than 3,000 people across our London, Southampton, Cardiff and Manchester offices. We are looking for a talented and passionate Model Validation Senior Analyst to join our Model Risk Oversight Team. The team focuses on validating and overseeing the risks associated with all … models across Starling, particularly those involving advanced modeling techniques (including AI). If you have model validation/model build experience and are eager to be part of the team that plays a vital role in model risk management, we want to hear from you! As … a Senior Analyst - Model Validation, with the support from your manager, you will be responsible for: Validating different types of models used across Starling, such as IFRS 9, Forecasting, Operational Risk, AI/ML models. Producing validation reports whilst engaging with the model developers and model More ❯

Model Validation Quant Contract OUTSIDE IR35 Quant Capital is urgently looking for a Model Validation Quant to join our high profile client. Our client is a Tier 1 Investment Bank. This is a first-line quant role — embedded with the quant desk and directly shaping modelling … them after the fact. This isn’t just about implementing models. It’s about being the person who sees the cracks before they become validation blockers. We need someone who can: • Challenge model assumptions • Spot weaknesses in structure, calibration, or data • Write documentation that defends the model with clarity and depth You’ll work closely with FO quants, guide their submissions, and act as a bridge to model validation — pre-empting issues before they escalate. Responsibilities: • Review and guide FO quant model submissions with a critical eye • Develop, test, and refine models using More ❯

models. Making key analytical decisions regarding market risk modelling for Equity derivatives positions traded in Europe and Asia. Assessing appropriateness of the market risk model outputs by performing time series review and stationarity test, Basel traffic light backtesting and VaR breaches explanation, P&L attribution test, pricing model benchmark, and quantification of the materiality of any model limitations (e.g. RNIV). Documenting model implementation details, tests, and findings for model validation to review, in accordance with Firm’s Model Risk Management policies and framework. Qualifications: Strong background in market risk models and … results). Excellent communication and presentation skills (ability to engage in concise, effective discussions). Excellent written skills (ability to produce well-structured technical model documentation). Ability to work without significant direct supervision. Previous experience of regulatory capital model & economic capital model is preferred. Knowledge of More ❯

of forecasting models, including time series and machine learning, implementing “what-if” scenarios for capacity planning and demand variability. Core areas of responsibility; Forecasting model development Data management Model selection and validation Model deployment and maintenance Data Scientist Candidate Requirements: Post study experience as Data Scientist More ❯

and its application to risk management in banking You will have strong Wholesale IRB background (essential) with hands-on experience in IRB credit risk model development, and a strong understanding of IRB approval process and existing regulations are a must, along with familiarity with both local and relevant international … regulations within financial services e.g. PRA/ECB supervision Possess hands-on experience in Wholesale IRB credit risk model building and/or validation (i.e., beyond audit or review activities) - the interview process will involve a deep dive into the technical knowhow of modelling, validation techniques and … Spain, Middle East, Netherlands, South Africa, my client is a boutique firm with a demonstrable focus around Credit Risk Management, modelling, data analytics and model validation etc. Working with a range of innovative, ambitious, growing and forward-thinking Financial Services businesses, my client differentiates itself from the larger More ❯

the solutions that the team delivers -Present findings and recommendations to technical and non-technical audiences. -Acquire domain knowledge to inform modelling opportunities and model feature creation Technical Leadership: -Mentor junior data scientists and provide peer reviews for modelling projects. -Stay current with industry trends, tools, and best practices More ❯

doing? • Advising clients on the impact of changing requirements in provision accounting standards (IFRS9) and Basel credit risk capital requirements (IRB). This will model review and validation activities such as: • Technical model development documentation review; • Assessment of model performance • Replication testing; and • Reviewing models’ against … accounting and risk requirements as related to IRB, IFRS9, and other regulatory credit risk models • Detailed working knowledge and experience of all aspects of model development and validation including the following: • Data extraction and pre-processing • Modular model development • User acceptance testing • Model performance assessments • Relevant More ❯

initial 6 month contract + opportunity to extend long-term & start date May 2025. Role Summary: Lead data activities including extraction, transformation, analysis, and validation to support Marketing Mix Modelling (MMM). Build, enhance, and validate models to analyze KPIs and guide budget optimization and scenario planning. Key Responsibilities More ❯

technical stakeholders. Write robust, production-ready Python code and partner with technology teams to operationalise models. Ensure models are compliant with internal governance and model risk frameworks. Provide ongoing model validation, documentation, and performance monitoring. Ideal Candidate Will Have: Strong background in ALM or Treasury modelling, particularly More ❯

strong analytical mindset and prefer working behind the scenes with data Leading the modelling process from briefing, data exploration, and variable selection through to model building, interpretation, and being involved in the presentation of results (interim and final debriefs will be presented by the Account Director) Creating clear and … presentations Experience & Skills Required Strong econometric modelling skills using tools such as R, Python, or other statistical software packages (e.g., EViews, SAS) Experience with model validation, diagnostics, and performance metrics Ability to handle large datasets, clean and transform raw data, and apply advanced statistical techniques such as regression … saturation, and interaction effects The successful candidate will be expected to take full ownership of modelling projects, from raw data ingestion through to final model delivery and client-ready outputs, with minimal supervision. If this sounds like you then please apply! Alternatively, you can refer a friend or colleague More ❯

be doing: Spotting opportunities to apply data science and ML to solve meaningful product challenges Designing and building data pipelines to support experimentation and model development Running structured experiments and analysing performance metrics to validate outcomes Deploying and maintaining models in production and delivering clear business impact Collaborating closely … engineering, and business stakeholders What you’ll bring: Hands-on experience developing and productionising ML models Strong analytical background with applied stats, EDA, and model validation techniques Confidence working with structured data pipelines and modern tooling (AWS, Snowflake, Airflow, DBT) Curiosity for emerging techniques and an eagerness to More ❯

are reliable, efficient, and scalable. Responsibilities: Develop browser extensions and desktop apps (Windows and MacOS). Create web apps for AI agent audits and model performance validation. Design and implement robust pipelines for AI models - for reliability and scalability. Write clean, maintainable, defensible, and scalable code with a high More ❯

Lake + OLAP) in AWS Develop scalable data pipelines in Python , working with SDKs and data libs Own end-to-end data modeling , ingestion, validation, and optimization for high-concurrency access Tune performance of cross-region, multi-format data stores (columnar, real-time, etc.) Deliver tailored solutions directly to More ❯

level. Design of FPGA hardware (generally using the latest AMD FPGAs, including Versal). Development and debug of FPGA VHDL code. Design, testing and validation of high-speed serial interfaces such as PCIe, Aurora, JESD, and Ethernet. Design of interfaces and control blocks for HW components such as ADC More ❯

epigenomics, and metabolomics—to capture comprehensive cellular signatures. Your work will enable precise predictions of drug effects, driving innovation in drug discovery. Key Responsibilities: • Model Development: Design deep learning models integrating diverse omics data to create robust cell embeddings for digital twin technology. • Multi-Omics Integration: Develop and refine More ❯

for our clients. You will work closely with senior colleagues to support the efficient delivery of projects, including data collection and preparation, contributing to model finalization, writing results, and supporting the development of other analysts. You will also be expected to develop strong relationships with clients and communicate Gain … gain technical skills and knowledge of our working practices and methodologies. Key responsibilities include: Working with data: Data extraction and manipulation, data analysis and validation, batch files, programming Undertake data extraction, manipulation, and data analysis to understand the marketplace and client context relevant to each project. Analyse all datasets … process, transform, create variables and build models. Be or be working towards expert knowledge in a selection of these tools/approaches. Building Models: Model building and validation, sales effects calculations, ROIs, media optimisation Building of base models according to the project specification, incorporating all drivers of KPIs More ❯

to support generative AI workflows and large language models (LLMs) in production. What You’ll Do Design, build, and maintain scalable ML platforms for model development, experimentation, and production workflows. Automate ML infrastructure deployment, including data pipelines, model training, validation, and deployment. Manage the full ML lifecycle … from model versioning to deployment, monitoring, and retraining. Optimise large language model (LLM) operations , ensuring efficient fine-tuning, deployment, and performance monitoring. Collaborate closely with data scientists and engineers to develop and deploy ML models at scale. Optimise performance for inference and training across GPUs and cloud-based … handling sensitive data. Evaluate and integrate MLOps tools (MLflow, Kubeflow, etc.) to enhance efficiency. Implement monitoring and alerting systems to detect anomalies and maintain model reliability. What We’re Looking For 3+ years of experience in software engineering, infrastructure, or MLOps roles. Proven expertise in building and maintaining ML More ❯

development of analysts through the Training Academy, Knowledge Shares and feedback. Key responsibilities include: Working with data: Data extraction and manipulation, data analysis and validation, batch files, programming Undertake data extraction, manipulation, and data analysis to understand the marketplace and client context relevant to each project. Analyse all datasets … process, transform, create variables and build models. Be or be working towards expert knowledge in a selection of these tools/approaches. Building Models: Model building and validation, sales effects calculations, ROIs, media optimisation Building of base models according to the project specification, incorporating all drivers of KPIs … providing rationale for variables entered, understanding coefficients and SFX. Taking base models, oversee or build in additional improvements and progress the model towards finalisation. Calculate sales effects throughout the project to check results and assess their correctness, i.e., does media contribution make sense? Report to project team on preliminary More ❯

Job Description Hybrid: This role is categorized as hybrid. This means the successful candidate is expected to report to Concord, NC three times per week, at minimum. Given the need to support some live race events during weekends, this role More ❯

Job Description Hybrid: This role is categorized as hybrid. This means the successful candidate is expected to report to Concord, NC three times per week, at minimum. Given the need to support some live race events during weekends, this role More ❯

Job Description Hybrid: This role is categorized as hybrid. This means the successful candidate is expected to report to Concord, NC three times per week, at minimum. Given the need to support some live race events during weekends, this role More ❯

Job Description Hybrid: This role is categorized as hybrid. This means the successful candidate is expected to report to Concord, NC three times per week, at minimum. Given the need to support some live race events during weekends, this role More ❯

Job Description Hybrid: This role is categorized as hybrid. This means the successful candidate is expected to report to Concord, NC three times per week, at minimum. Given the need to support some live race events during weekends, this role More ❯

Job Description Hybrid: This role is categorized as hybrid. This means the successful candidate is expected to report to Concord, NC three times per week, at minimum. Given the need to support some live race events during weekends, this role More ❯

Job Description Hybrid: This role is categorized as hybrid. This means the successful candidate is expected to report to Concord, NC three times per week, at minimum. Given the need to support some live race events during weekends, this role More ❯