1 to 25 of 39 Model Validation Jobs in Central London

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 ❯

What You’ll Be Doing: Designing and building machine learning models to solve real-world problems Carrying out full data science workflows: from data acquisition and cleaning to modelling, validation, and deployment Applying statistical and AI techniques to generate actionable insights Contributing to experimental research, model prototyping, and A/B testing Presenting findings clearly to both technical … a related discipline Strong programming skills in Python (e.g. NumPy, pandas, scikit-learn, matplotlib); R is also welcome A solid understanding of core machine learning concepts, data wrangling, and model evaluation Proficiency with SQL and experience handling large datasets A passion for solving complex problems using data and a continuous learning mindset Excellent communication and collaboration skills Full right More ❯

learning, and data science, particularly in the LLM field, and share knowledge with the team. Contribute to the creation of AI research pipelines, ensuring high data quality standards, rigorous model validation, and comprehensive performance evaluation. Mentor and guide junior engineers and researchers, fostering a culture of innovation and collaboration. Qualifications Master's degree in Computer Science, Artificial Intelligence More ❯

the globe to ensure we deliver best in class risk prevention solutions Your key responsibilities Develop a thorough understanding of the data science lifecycle, including data exploration, preprocessing, modelling, validation, and deployment. Design, build, and maintain tree-based predictive models, such as decision trees, random forests, and gradient-boosted trees, with a low-level understanding of their algorithms and … machine learning models to optimize performance. Collaborate with cross-functional teams to understand business needs and provide data-driven solutions and insights. Conduct A/B testing and other model validation techniques to ensure the accuracy and reliability of data models. Communicate complex data insights to non-technical stakeholders through clear and actionable reports. Apply domain knowledge (if More ❯

financial decisions across global markets. Responsibilities: Lead the development and maintenance of credit risk and affordability models using bureau, open banking, and alternative behavioural data. Own end-to-end model lifecycle: data sourcing, feature engineering, model development, validation, and monitoring. Design and execute champion/challenger tests and A/B experiments to continuously improve approval rates … of analysts/data scientists as the team scales Work closely with Data Engineering to deploy models into production pipelines. Collaborate with stakeholders to define modelling goals and interpret model outcomes in a business context. Requirements: MSc or PhD Degree in Computer Science, Artificial Intelligence, Mathematics, Statistics or related fields. Strong coding skills in Python and SQL Strong communication More ❯

both qualitatively and quantitatively to ensure they meet rigorous scientific standards. Contribute to building our overall loss modelling framework, ensuring robustness and adaptability across diverse client requirements and geographies Model documentation and presentations to engage with stakeholder and customers, all while representing the team at international conferences and industry events Requirements: MSc or PhD Degree in Computer Science, Artificial More ❯

work permit required: Yes col-narrow-right Job Views: 2 Posted: 07.06.2025 Expiry Date: 22.07.2025 col-wide Job Description: Head of Quantitative Risk Analytics – Quantitative Finance, Counterparty Credit Risk, Model Development, Model Validation, Risk Analysis, Python, R, SQL, Numerix, - City of London, Permanent A senior Quantitative Specialist is sought after by a Global Investment Bank to take … modelling function, as part of the wider Risk Analytics group. In this role, you will be responsible for managing the end-to-end modelling lifecycle, being responsible for methodology, model design and development, through to implementation and validation, helping support local Counterparty Credit Risk Management. This will be a multi-functional role, with responsibility for building and maintaining … research to keep models up to date ensuring the business have access to accurate analytics. You will work closely with the business and other quantitative specialists for a cohesive model development process, including the implementation of highly accessible tools and dashboards for users to effectively undertake risk analysis. To be successful, you will demonstrate: Minimum of a Master’s More ❯

pay will be based on your skills and experience — talk with your recruiter to learn more. Base pay range Head of Quantitative Risk Analytics – Quantitative Finance, Counterparty Credit Risk, Model Development, Model Validation, Risk Analysis, Python, R, SQL, Numerix, - City of London, Permanent A senior Quantitative Specialist is sought after by a Global Investment Bank to take … modelling function, as part of the wider Risk Analytics group. In this role, you will be responsible for managing the end-to-end modelling lifecycle, being responsible for methodology, model design and development, through to implementation and validation, helping support local Counterparty Credit Risk Management. This will be a multi-functional role, with responsibility for building and maintaining … research to keep models up to date ensuring the business have access to accurate analytics. You will work closely with the business and other quantitative specialists for a cohesive model development process, including the implementation of highly accessible tools and dashboards for users to effectively undertake risk analysis. To be successful, you will demonstrate: Minimum of a Master’s More ❯

Calibrate confidence metrics with historical data and measure their value to trading & risk learning models. Continuously improve these models based on real-time data and feedback from trading activities. Model Communication: Explain uncertainty clearly, turning numbers into concise narratives and action-oriented alerts Broader Contributions: Build and refine statistical/ML models for short- to medium-term demand, renewables … output, and other fundamental time series. Help design feature pipelines, scenario tools and model-performance dashboards used daily by traders and analysts. Pitch in on ad-hoc analytics projects—anything from volatility clustering studies to optimisation of storage dispatch—whenever the desk needs statistical horsepower. REQUIREMENTS: Minimum of a degree in Statistics, Applied Maths, Physics or related field. Minimum More ❯

Independent model validation of quantitative methodologies, both initial and periodic, across all asset classes and model types (derivative pricing models, credit and market risk, capital models, AI models, etc. ) and in line with regulatory requirements and industry best practice. The validation regularly requires an independent implementation of the models and the implementation of alternative challenger models. … KEY RESPONSIBILITIES Initial and periodic validation of quant models Designing, modelling and prototyping challenger models Quantitative analysis and review of model frameworks, assumptions, data, and results Testing models numerical implementations and reviewing documentations Checking the adherence to governance requirements Documentation of findings in validation reports, including raising recommendations for model improvements Ensuring models are validated in … line with regulatory requirements and industry best practice Tracking remediation of validation recommendations SKILLS AND EXPERIENCE Essential: At least a first relevant experience in quantitative modelling (model development or validation) in one or more of these topics: Market risk models Counterparty credit risk models Derivatives pricing models Optional: Capital models (Economic/Regulatory) Corporate credit risk models More ❯

servers, audience panels) for analysis. Statistical Analysis: Utilise econometric techniques like regression analysis, time series modelling, and panel data analysis to identify relationships between media spend and business outcomes. Model Validation and Interpretation: Evaluate the accuracy and robustness of models, interpret results, and communicate findings to stakeholders in a clear and concise manner. Campaign Optimisation: Provide data-driven … insights to inform media buying strategies, including channel allocation, budget optimisation, and creative testing. Advanced Analytics: Explore new data analysis techniques like machine learning to enhance model accuracy and uncover deeper insights. Your Experience and Skills: Data Science: Proficient in programming languages like Python, R, and SQL including data manipulation, data imputation, statistical modelling, and visualisation libraries. Econometrics Background More ❯

validating APIs and UIs for performance, reliability, and correct functionality. Ensure that both the backend (APIs) and the user-facing interfaces meet the product's functional and quality standards. • Model Testing & Validation: Ensure the quality of AI models by collaborating with data scientists and engineers. Conduct tests to validate model performance, reliability, and accuracy in real-world More ❯

ability to work closely with traders, quantitative researchers, and other developers. Key Responsibilities Algorithm Development: Design, develop, and optimize trading algorithms for equities and futures markets using C++. Quantitative Model Implementation: Collaborate with quantitative researchers to translate mathematical models into robust, efficient, and scalable code. System Performance Optimization: Ensure high performance and low latency of trading systems through rigorous … optimization and testing of C++ code. Backtesting and Simulation: Develop tools and frameworks for backtesting trading strategies and running simulations to validate model performance. Data Analysis: Analyze large datasets to identify patterns, trends, and opportunities that can inform trading strategies. Collaboration: Work closely with traders, quants, and other developers to integrate new features and enhancements into the trading platform. More ❯

This role is ideal for someone experienced in natural catastrophe modelling and confident working with large geospatial and financial loss datasets. You’ll contribute to the development, calibration, and validation of loss models that project climate-related physical impacts such as floods, subsidence, storms, droughts, and wildfires — helping clients assess and manage climate risks effectively. Key Responsibilities Develop loss More ❯

I'm currently supporting a fast-growing digital bank. Their Model Risk Oversight Team is looking for a talented Senior Analyst to focus on model validation – covering everything from IFRS 9 and forecasting to operational risk and AI/ML models. 🔍 What you’ll be doing: Validating diverse models across the bank Writing clear, actionable validation reports Presenting findings to committees and working closely with developers and stakeholders Helping shape model governance throughout the model lifecycle 🛠 What we're looking for: 2–3 years’ experience in model validation or development Proficiency in Python, R, SQL, SAS or similar tools Strong communication skills and analytical mindset Bonus: Familiarity with regulatory frameworks (EBA More ❯

SENIOR CREDIT MODEL VALIDATION ANALYST £65,000 LONDON/MANCHESTER THE COMPANY This successful FinTech has been growing significantly and has exciting plans and projects in the pipeline. They are at the forefront of the financial space and this role offers a chance for someone to work on hands-on model validation across their regulatory and … opportunity offers the rare chance to help grow the business and get involved in a range of modelling projects. THE ROLE Within this, you can expect to work on: Validation of models across the bank, including IFRS9, Treasury, Scorecards and Forecasting Development of challenger models as necessary to enhance this area of the bank Supporting other teams across the … implementation and wider maintenance of these models Working closely with the broader bank to implement Machine Learning and AI models YOUR SKILLS AND EXPERIENCE Essential to have experience in model development or validation Exposure to IFRS9 and wider credit models is essential Experience in Python/SQL/SAS/R Educated to at least degree level in More ❯

the intersection of quantitative research, machine learning, and software engineering. You'll collaborate with quants, data scientists, and portfolio managers to design and implement scalable systems for data ingestion, model training, and real-time signal deployment. Key Responsibilities Design and develop robust, high-performance systems for AI/ML model development and deployment. Collaborate with quantitative researchers to … translate trading strategies into production-ready code. Build and maintain data pipelines for structured and unstructured financial data. Implement backtesting frameworks and simulation environments. Optimise model inference and execution latency for real-time trading. Contribute to architectural decisions and technology stack selection for the greenfield platform. Required Skills & Experience Strong programming skills in Python, with experience in production-grade … systems. Solid understanding of machine learning workflows, including model training, validation, and deployment. Experience with quantitative finance, including time series analysis, alpha modelling, or risk analytics. Familiarity with cloud infrastructure (e.g., AWS, GCP) and containerisation (Docker, Kubernetes). Proficiency with data engineering tools Experience working in fast-paced, collaborative environments with agile methodologies. Nice to Have Prior experience 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 ❯

deploy high-quality AI/ML capabilities. ● Research and evaluate new AI/ML algorithms and technologies. ● Collaborate with data scientists to prepare and engineer high-quality datasets for model training and evaluation. ● Develop and maintain robust and scalable machine learning pipelines. ● Conduct rigorous model validation and performance monitoring. ● Ensure the ethical and responsible use of AI 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 ❯

the business. What you’ll 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 with product, 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 learn and innovate Excellent communication skills, especially when simplifying complex findings for non More ❯

daily (Umbrella) Our client is hiring two experienced Data Scientists to join our fast-growing UK Data & AI practice . You’ll be at the forefront of machine learning model development for leading insurance and financial services clients , working in a collaborative, hands-on environment. 📍 Location: London (Hybrid: 2–3 days onsite per week) 📅 Start: Early July 2025 💼 Type … Contractor 💰 Salary: Up to £78,000 or £350/day equivalent 🧠 Your Profile: 6–10 years of experience in Data Science & ML Expert in Python , data wrangling, EDA, modelling, validation, and deployment Strong in supervised & unsupervised learning ; exposure to NLP/OCR a plus Proficient with AWS SageMaker , Databricks ; Palantir Foundry/AIP is a big plus Insurance/ More ❯

rare conditions. We’re looking for a principal computational biologist or data scientist to play a critical role in this project — leading the analyse of image-based embeddings, validating model outputs, and collaborating closely with ML engineers and vision scientists to ensure the biology behind the model holds up. Must Haves: PhD in Computational Biology, Bioinformatics, Systems Biology … and analysing multi-modal biological data, such as transcriptomics, proteomics, or single-cell data. Proficiency in Python, including libraries such as Pandas, NumPy, scikit-learn Experience analysing deep learning model outputs, especially from vision models and working with biological image embeddings. Ability to evaluate model performance, interpret model outputs, and connect them to biological hypotheses. Demonstrated ability … biological or image data. Familiarity with deep learning frameworks (e.g., PyTorch or TensorFlow). Familiarity with cell-level microscopy (e.g., Cell Painting, HCS) and downstream biological interpretation. Understanding of model feedback loops — such as collaborating with ML teams to refine models based on biological relevance. Strong grasp of data visualization tools and techniques for communicating multi-dimensional biological findings. More ❯

MODEL VALIDATION MANAGER COMPETITIVE SALARY UP TO £80,000 LONDON, HYBRID WORKING (2-3 DAYS A WEEK IN OFFICE) In this role, you’ll be leading a talented team of analysts to validate a range of models across the business, including ML, AI, IFRS9, and Forecasting. You’ll be leading Risk Assurance reviews and presenting high-level validation … experiencing consistent levels of growth. You’ll be working within a highly talented team and have the opportunity to drive real change. THE ROLE Validate and support in the validation of various models across the business, from more traditional models like IFRS9 and Forecasting, to AI and ML models. Engage with model owners and developers to ensure validation … findings are accurate and understood Lead the Risk Assurance reviews and produce committee papers to present to senior stakeholders YOUR SKILLS AND EXPERIENCE Strong experience in the Credit Risk Model Validation space AI Model knowledge and experience are required Proficiency in either SQL, SAS, or Python Management experience THE BENEFITS Competitive salary up to £80,000 Hybrid More ❯