4 of 4 Model Validation Jobs in the City of Westminster

the candidate needs to be truly, technically competent, to be able to quickly learn a complex system, customise source code, add in new features and code from scratch. Whilst model deployment/software development experience is very, highly desirable, we do have a team of engineers to support so exposure in this space will be sufficient. Culture-wise, we … . Key Responsibilities: Further improve existing algorithms and develop net new DS features Design and contribute to the end-to-end machine learning pipeline from data collection, reprocessing to model training, simulation, evaluation, deployment and experimentation/testing Implement and interpret explainability frameworks to provide clear insights into model decisions, ensuring transparency and compliance with WPP standards Collaborate … with stakeholders to identify business needs and translate these requirements into technical solutions that are scalable and impactful Conduct rigorous model testing and validation to ensure robustness and accuracy Prepare detailed documentation and reports that communicate complex model behaviours, predictions, and insights in a manner accessible to both technical and non-technical audiences Stay abreast of academic More ❯

small and large-sized multidisciplinary engagement teams delivering quantitative finance projects for clients: Cross-asset derivative pricing including valuation adjustments (XVA). Calibration of models using best industry practices Model validation for small to large size clients, for quantitative risk management models such as (PD/LGD, VaR, Expected Shortfall, EPE/PFE) Implementation review of accounting standards … market (VaR, Expected Shortfall, FRTB) risk modelling Strong experience in using either of Python, R or C++ Ability to work in a team and individually Desired experience/skills: model validation and machine learning About Forvis Mazars Forvis Mazars is a leading global professional services network. The network operates under a single brand worldwide, with just two members More ❯

quality assurance, and ongoing system improvement. Job Responsibilities: Build and integrate ML models into structured backend services (APIs, pipelines, batch processors). Write production-ready Python code to support model inference, validation, and logging. Assist in building automated workflows for data ingestion, model deployment, and metadata tagging. Build dashboards, logs, or simple UI tools to visualize and … or related field. Commercial software development experience, ideally with exposure to ML/AI systems. Strong programming skills in Python; familiarity with web frameworks (Flask, FastAPI). Understanding of model inference lifecycles, APIs, and data validation. Familiarity with Git, CI/CD pipelines, testing, and performance profiling. Ability to work independently and deliver clean, maintainable, production-quality code. Preferred More ❯

quality assurance, and ongoing system improvement. Job Responsibilities: Build and integrate ML models into structured backend services (APIs, pipelines, batch processors). Write production-ready Python code to support model inference, validation, and logging. Assist in building automated workflows for data ingestion, model deployment, and metadata tagging. Build dashboards, logs, or simple UI tools to visualize and … or related field. Commercial software development experience, ideally with exposure to ML/AI systems. Strong programming skills in Python; familiarity with web frameworks (Flask, FastAPI). Understanding of model inference lifecycles, APIs, and data validation. Familiarity with Git, CI/CD pipelines, testing, and performance profiling. Ability to work independently and deliver clean, maintainable, production-quality code. Preferred More ❯