1 to 25 of 186 Model Validation Jobs in the UK excluding London

and measurable outcomes Demonstrate system-level thinking, considering architectural choices, data dependencies and integration across the wider data platform Develop and maintain production-grade ML systems including retraining strategies, model lifecycle management, monitoring and alerting Act as a trusted technical authority, reviewing and challenging project design, methodology, and outputs Drive adoption of CI/CD practices, unit testing, and … for tooling, technologies and approaches that support scalable, sustainable data science delivery Mentor and develop less experienced data scientists, fostering technical and professional growth Champion ethical AI, explainability and model governance throughout the lifecycle of our solutions Contribute to a culture of continuous learning, experimentation and data-informed decision making Skills and Qualifications: We are looking for those who … e.g. logistic regression, random forest, XGBoost, and modern deep learning techniques (e.g. transformers, transfer learning, reinforcement learning) Proven ability to lead technical direction across projects or domains Expertise in model validation, explainability, governance and ethical AI principles Advanced proficiency in Python (e.g. Scikit-learn, TensorFlow/PyTorch) and SQL, plus familiarity with ML engineering and MLOps practices Nice More ❯

actionable insights for stakeholders. Collaborate with cross-functional teams including marketing, merchandising, and supply chain. Mentor and support junior data scientists and analysts. Promote best practices in data science, model validation, and experimentation (e.g., A/B testing). Key Requirements: Proven experience (5+ years) in a data science role, preferably in retail or e-commerce sectors. Strong More ❯

solve business problems but do so optimally. Additionally, you're not just building and validating models – you’re deploying them as code to applications and processes, ensuring that the model(s) you've selected sustains its business value throughout its lifecycle. Your expertise doesn't stop at data; you'll become intimately familiar with our business processes and have More ❯

analysis to assess and predict financial risks including input into regulatory processes/reporting. Provide regular reports and insights to senior leadership, highlighting emerging risks and their potential impact. Model Risk Management (including statistical, advanced AI/ML based techniques) - Formulation of guidelines/policy, laying down of roadmap, establishment of model risk governance including frameworks, validation … GAAP) and regulatory requirements (e.g., Basel III, IFRS 9). Statistical Techniques: Linear & Logistic Regression, Hypothesis Testing, Exploratory Data Analysis, Survival Analysis, Cluster Analysis, various Statistical Tests and Cross-Validation Techniques, ML Algorithms. Proficiency in programming languages like Python, R, or MATLAB for quantitative modeling. Soft Skills: Strong analytical and problem-solving skills with attention to detail. Ability to 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 ❯

organizations, and other enabling functions. To be successful, the ideal candidate will demonstrate a thirst for knowledge and a natural curiosity to enable rapid learning of the Zoetis business model and data & analytics infrastructure at a scale to support a growing business. The position requires a candidate who is comfortable translating and connecting the business context to the technical … and trends within datasets. Translate insights to actionable recommendations aligned with business objectives. Design business intelligence and analytics tools to track business performance across marketing, sales, and retail organizations. Model Development and Optimization Build advanced analytics to extract key strategic insights (product, customer, etc..) to inform key strategic decisions. Build, test and validate predictive models to support business needs. … Implement and maintain machine learning models in production environment. Monitor model performance and refine algorithms to ensure accuracy and relevance. Partner with Data Governance to implement data governance framework to improve data quality, better decision-making and increased operational efficiency. Stakeholder Engagement Collaborate with senior leaders to identify opportunities for business growth and assist in implementing data-driven strategies More ❯

security, and improved quality of life. Are you excited at the opportunity to electrify and decarbonize the world? We are seeking a highly skilled and results-driven Data Scientist - Validation to join our team, primarily focusing on validating AI/ML models for grid innovation applications. This role will involve rigorous testing, validation, and verification of AI/… environments. Job Description Essential Responsibilities: Design and conduct experiments to test and validate AI/ML models in the context of energy systems and grid automation applications. Establish clear validation frameworks to ensure models meet required performance standards and business objectives. Establish test procedures to validate models with real and simulated grid data. Analyze model performance against real … world data to ensure accuracy, reliability, and scalability. Identify and address discrepancies between expected and actual model behavior, providing actionable insights to improve model performance. Implement automated testing strategies and pipeline to streamline model validation processes. Collaborate with Data Engineers and ML Engineers to improve data quality, enhance model performance, and ensure efficient deployment of More ❯

drive strategic marketing decisions—optimizing media budgets, forecasting business performance, and supporting commercial objectives through rigorous analytical frameworks. Key Responsibilities Lead the full econometric modelling lifecycle: data extraction, transformation, model building, validation, and business interpretation. Build and refine Marketing Mix Models (MMM) with robust statistical foundations and clear KPI linkages. Generate actionable outputs such as ROI analyses, response … curves, and optimization tools. Perform scenario simulations for budget allocation, marketing strategy, and planning. Conduct model diagnostics, ensure methodological robustness, and continuously improve model accuracy. Required Skills & Experience Demonstrable experience in Marketing Mix Modelling (MMM) and econometrics, ideally within FMCG or related sectors. Strong command of Python and pandas; working knowledge of R is also a plus. Proficient More ❯

analysis to assess and predict financial risks including input into regulatory processes/reporting. Provide regular reports and insights to senior leadership, highlighting emerging risks and their potential impact. Model Risk Management (including statistical, advanced AI/ML based techniques) - Formulation of guidelines/policy, laying down of roadmap, establishment of model risk governance including frameworks, validation … GAAP) and regulatory requirements (e.g., Basel III, IFRS 9). Statistical Techniques: Linear & Logistic Regression, Hypothesis Testing, Exploratory Data Analysis, Survival Analysis, Cluster Analysis, various Statistical Tests and Cross-Validation Techniques, ML Algorithms. Proficiency in programming languages like Python, R, or MATLAB for quantitative modeling. Soft Skills: Strong analytical and problem-solving skills with attention to detail. Excellent communication More ❯

learning, statistical, optimisation and econometric methods to business problems. You'll contribute to the research and implementation of new approaches to address complex problems and perform data analysis and model validation. You'll also have the opportunity to present results to both internal teams and clients. What you'll be working on Developing innovative methods to exploit dunnhumby's … world class Price & Promotions capabilities Supporting our high-performing Price & Promotions experts by implementing new capabilities with significant business impact Performing exploratory data analysis and model validation What we expect from you Master's degree/PhD in Computer Science, Machine Learning, Applied Statistics, Physics, Engineering or related field Strong mathematical and statistical skills Experience with Python, Spark More ❯

models and advanced analytics solutions. Collaborate cross-functionally to identify and prioritize data science opportunities. Build and mentor a high-performing data science team. Establish best practices for experimentation, model validation, and deployment. Communicate complex data insights to technical and non-technical stakeholders. Stay current with trends in data science, machine learning, and financial technologies. Requirements Bachelor’s More ❯

learning, statistical, optimisation and econometric methods to business problems. You’ll contribute to the research and implementation of new approaches to address complex problems and perform data analysis and model validation. You’ll also have the opportunity to present results to both internal teams and clients. What you’ll be working on Developing innovative methods to exploit dunnhumby’s … world class Price & Promotions capabilities Supporting our high-performing Price & Promotions experts by implementing new capabilities with significant business impact Performing exploratory data analysis and model validation What we expect from you Master’s degree/PhD in Computer Science, Machine Learning, Applied Statistics, Physics, Engineering or related field Strong mathematical and statistical skills Experience with Python. Spark More ❯

through advanced econometric modelling—including Bayesian Marketing Mix Modelling (MMM), Multi-Touch Attribution (MTA), and data-driven optimization strategies. Key Responsibilities Lead and manage data workflows: data extraction, transformation, validation, and exploratory analysis to ensure modelling-readiness. Build and refine Bayesian MMM models that capture the drivers of key marketing and commercial KPIs. Use Python (and optionally R) to More ❯

for our Financial Services client. Key Responsibilities End-to-End AI Solution Delivery: Lead AI/ML initiatives from conceptual design to production deployment, including problem scoping, data acquisition, model development, validation, deployment, and monitoring. AI-Driven Marketing Insights: Develop predictive and generative models to support audience segmentation, personalization, channel optimization, lead scoring, and campaign measurement. Collaborative Development … Work closely with marketing strategists, data analysts, data engineers, and product owners to define use cases and deliver scalable solutions. Model Deployment & Monitoring: Deploy models using MLOps practices and tools (e.g., MLflow, Airflow, Docker, cloud platforms) ensuring performance, reliability, and governance compliance. Innovation & Research: Stay current on advancements in AI/ML and proactively bring forward new ideas, frameworks … techniques that can be applied to marketing use cases. Data Strategy: Collaborate with data engineering teams to ensure the availability of clean, structured, and enriched data pipelines required for model training and inference. Required Qualifications Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, Applied Mathematics, or a related field. 4+ years of experience in More ❯

sales engagements performing a range of tasks from supporting a technical sales strategy for a new client, communicating the value of our software towards industry challenges, software installs, process model design, workflow design, data manipulation, and problem solving. Technical teaching and consulting are also part of the job. Key Responsibilities Work with subject experts from operations, manufacturing, and business More ❯

solve business problems but do so optimally. Additionally, you're not just building and validating models – you’re deploying them as code to applications and processes, ensuring that the model(s) you've selected sustain business value throughout their lifecycle. Your expertise doesn't stop at data; you'll become intimately familiar with our business processes and have the More ❯

process maps and target operating models to enhance clarity and efficiency. Data analysis and definition, e.g. data-led insights, development of data dictionaries and data models . Supporting the validation of solutions delivered against acceptance criteria, through test planning, execution, coordination, etc. Partner ing with Architects or Development teams to produce appropriate design specifications Continuously review and assess solution More ❯

electricity for health, safety, and security. Are you excited about the opportunity to electrify and decarbonize the world? We are seeking a highly skilled and results-driven Data Scientist - Validation to join our team, focusing on validating AI/ML models for grid innovation applications. This role involves rigorous testing, validation, and verification of AI/ML models …/ML models in complex, data-rich environments. Essential Responsibilities: Design and conduct experiments to test and validate AI/ML models in energy systems and grid automation. Establish validation frameworks to ensure models meet performance standards and business objectives. Develop test procedures to validate models with real and simulated grid data. Analyze model performance against real-world … data for accuracy, reliability, and scalability. Identify discrepancies between expected and actual model behavior, providing insights for improvement. Implement automated testing strategies and pipelines to streamline validation processes. Collaborate with Data and ML Engineers to enhance data quality and model deployment. Ensure validation processes adhere to data governance policies and standards. Communicate validation results and More ❯

be given to candidates with a strong educational background and relevant certifications. Skills: Strong foundation in statistics and programming (R/Python). Experience with data preparation, visualisation, and model building. Knowledge of big data platforms (Hadoop, Spark) and SQL/NoSQL databases. Experience: 3+ years of experience as a Data Scientist or in a related role. Typical Responsibilities … and collecting the data required Manipulating, transforming, and cleaning the data A data scientist must deal with data anomalies such as missing values, outliers, unbalanced data, and data normalisation. Model building: This stage is the core of the data science execution, where different algorithms are used to train the data and the best algorithm is selected. A data scientist … should know: Multiple modelling techniques Model validation and selection techniques A data scientist must understand the use of different methodologies to gain insights from the data and translate those insights into business value. Model deployment: An ML model is valuable when it’s integrated into an existing production environment and used to make business decisions. Deploying More ❯

problems or opportunities. AI Strategy: Contribute to the organisation's AI strategy by identifying opportunities for leveraging AI technologies to drive innovation, improve business processes, and enhance decision-making. Model Development and Evaluation: Contribute to the development, deployment, and evaluation of AI models and to the deployment and evaluation of off the shelf AI models. Collaboration and Stakeholder Management … with organisational goals. Prototyping, developing, and deploying machine learning applications into production. Contributing to our machine learning enabled, business-facing applications. Contributing effective, high quality code to our codebase. Model validation and model testing of production models. Presenting findings to senior internal and external stakeholders in written reports and presentations. This role is for you if: Python … for API and Model development (Machine learning frameworks and tooling e.g. Sklearn) and (Deep learning frameworks such as Pytorch and Tensorflow). Understanding of machine learning techniques. Experience with data manipulation libraries (e.g. Pandas, Spark, SQL). Git for version control. Cloud experience (we use Azure/GCP/AWS). Skills we'd also like to hear about More ❯

problems or opportunities. AI Strategy: Contribute to the organisation's AI strategy by identifying opportunities for leveraging AI technologies to drive innovation, improve business processes, and enhance decision-making. Model Development and Evaluation: Contribute to the development, deployment, and evaluation of AI models and to the deployment and evaluation of off the shelf AI models. Collaboration and Stakeholder Management … with organisational goals. Prototyping, developing, and deploying machine learning applications into production. Contributing to our machine learning enabled, business-facing applications. Contributing effective, high quality code to our codebase. Model validation and model testing of production models. Presenting findings to senior internal and external stakeholders in written reports and presentations. This role is for you if: Python … for API and Model development (Machine learning frameworks and tooling e.g. Sklearn) and (Deep learning frameworks such as Pytorch and Tensorflow). Understanding of machine learning techniques. Experience with data manipulation libraries (e.g. Pandas, Spark, SQL). Git for version control. Cloud experience (we use Azure/GCP/AWS). Skills we'd also like to hear about More ❯

problems or opportunities. AI Strategy: Contribute to the organisation's AI strategy by identifying opportunities for leveraging AI technologies to drive innovation, improve business processes, and enhance decision-making. Model Development and Evaluation: Contribute to the development, deployment, and evaluation of AI models and to the deployment and evaluation of off the shelf AI models. Collaboration and Stakeholder Management … with organisational goals. Prototyping, developing, and deploying machine learning applications into production. Contributing to our machine learning enabled, business-facing applications. Contributing effective, high quality code to our codebase. Model validation and model testing of production models. Presenting findings to senior internal and external stakeholders in written reports and presentations. This role is for you if: Python … for API and Model development (Machine learning frameworks and tooling e.g. Sklearn) and (Deep learning frameworks such as Pytorch and Tensorflow). Understanding of machine learning techniques. Experience with data manipulation libraries (e.g. Pandas, Spark, SQL). Git for version control. Cloud experience (we use Azure/GCP/AWS). Skills we'd also like to hear about More ❯

you will be responsible for creating and curating the datasets for training and evaluating our ML planner components. You will build effective data analysis tools and work across ML model development and evaluation to achieve desired AV driving behaviours. You will also actively participate in operational support for your team, ensuring the root causes of operational issues are identified … You will: Take a leading role within your team to develop and deploy state of the art data pipelines for our machine learning models. Design and implement metrics for model validation and continuous monitoring in production. Leverage the Oxa Metadriver platform to generate synthetic data, and train effective and robust driving policies, Build cloud tooling and infrastructure in More ❯

you will be responsible for creating and curating the datasets for training and evaluating our ML planner components. You will build effective data analysis tools and work across ML model development and evaluation to achieve desired AV driving behaviours. You will also actively participate in operational support for your team, ensuring the root causes of operational issues are identified … You will: Take a leading role within your team to develop and deploy state of the art data pipelines for our machine learning models. Design and implement metrics for model validation and continuous monitoring in production. Leverage the Oxa Metadriver platform to generate synthetic data, and train effective and robust driving policies. Build cloud tooling and infrastructure in More ❯