26 to 50 of 258 Model Validation Jobs in the UK excluding London

Join to apply for the Senior Consultant, Model Risk Management role at Visa 5 days ago Be among the first 25 applicants Join to apply for the Senior Consultant, Model Risk Management role at Visa Visa is a world leader in payments and technology, with over 259 billion payments transactions flowing safely between consumers, merchants, financial institutions, and … being the best way to pay and be paid. Make an impact with a purpose-driven industry leader. Join us today and experience Life at Visa. Job Description The Model Risk Management (MRM) team at Visa has a mandate to validate business-impactful models firm-wide and more generally to identify, measure, and handle model risk across Visa. … The Senior Consultant, Model Risk Management will be responsible for conducting and assisting in model validations of models to strengthen model risk management capabilities at Visa. You will be responsible for: Identifying sources of risk in models. With minimal supervision conduct or assist with conducting validations of quantitative and complex financial models including AI/ML. Thoroughly 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 ❯

Pharmaceutical domain At least 2 years of experience in data engineering, including one or more of the following: relationship databases, data warehousing, data schemas, data stores, data modeling, testing, validation, and analysis Full professional proficiency in English Strong analytical and logical thinking Excellent communication and collaboration skills Nice to have: SAS programming experience with SQL programming SAS programming experience … Programming Department Knowledge of CDISC SDTM Experience with CluePoints RBM system Knowledge of statistical methods and techniques for analyzing data Experience using Machine Learning techniques and products testing and validation Additional Information What we offer: We value your time, so the recruitment process is as quick as 3 meetings Extensive onboarding and mentorship programs to prepare you for your More ❯

domain At least 2 years of experience in data engineering area including one or more of the following: relationship databases, data warehousing, data schemas, data stores, data modeling, testing, validation and analysis Full professional proficiency in English Strong analytical and logical thinking Communication and collaboration skills Nice to have: SAS programming experience with SQL programming SAS programming experience in … BiostatisticsDepartmentor Clinical Programming Department Knowledgeof CDISC SDTM Experience with CluePoints RBM system Knowledge of statistical methodsand techniques for analyzing data Experienceusing Machine Learning technics andproducts testing and validation Additional Information What we offer: We value your time so the recruitment process is as quick as 3 meetings We'll prepare you to do your job at highest quality level 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 ❯

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 ❯

power economies and deliver vital electricity for health, safety, and quality of life. Are you excited to electrify and decarbonize the world? We are seeking a skilled Data Scientist - Validation to join our team, focusing on validating AI/ML models for grid innovation applications. The role involves testing, validation, and verification of AI/ML models with … and improve AI/ML models in complex, data-rich environments. Job Responsibilities Design experiments to test and validate AI/ML models in energy and grid applications. Establish validation frameworks to meet performance and business objectives. Develop test procedures with real and simulated grid data. Analyze model performance to ensure accuracy and scalability. Identify and resolve discrepancies … providing insights for improvement. Implement automated testing pipelines for model validation. Collaborate with Data and ML Engineers to enhance data quality and model deployment. Ensure validation processes comply with data governance and industry standards. Communicate results and insights effectively to stakeholders. Minimum Requirements Degree in Data Science, Computer Science, Electrical Engineering, or related field with experience in 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 ❯

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 ❯

and refine your skills in Python (e.g., Pandas, NumPy) and SQL for data manipulation and analysis. Support the development of machine learning models and algorithms, assisting in testing and validation processes. Contribute to research efforts by exploring and applying the latest data science techniques. Collaborate with cross-functional teams to define and improve data collection and integration strategies. Assist More ❯

and healthcare applications. Lead the transition of machine learning research into viable prototypes and scalable production systems. Apply advanced techniques in natural language processing and machine learning to enhance model performance. Validate and test models to ensure readiness for real-world deployment. Build prototypes and take ownership from the design to the production of AI-powered products from client More ❯

and healthcare applications. Lead the transition of machine learning research into viable prototypes and scalable production systems. Apply advanced techniques in natural language processing and machine learning to enhance model performance. Validate and test models to ensure readiness for real-world deployment. Build prototypes and take ownership from the design to the production of AI-powered products from client More ❯

Senior Machine Learning Operation Engineers to join our Data Function. You'll play a significant role within our Data Function, working on the design and implementation of machine learning model engineering frameworks, solutions, and best practices. You'll be technically proficient in machine learning and its applications; you'll demonstrate an understanding of data management and show a keen … Engineering, Architecture, and Software Development to ensure efficient operation and use of Data Science models and will facilitate the full life cycle of machine learning models from data ingestion, model development, testing, validation, deployment, to monitoring and retraining of models within different environments. If you've a strong understanding of Microsoft Azure, fluency in data science coding, and … skills Powering the business with the right tools What's involved: You'll contribute to the design and implementation of Machine Learning Engineering standards and frameworks. You'll support model development, with an emphasis on auditability, versioning, and data security. You'll implement automated data science model testing and validation. You'll assist in the optimisation of deployed More ❯

Senior Machine Learning Operation Engineers to join our Data Function. You'll play a significant role within our Data Function, working on the design and implementation of machine learning model engineering frameworks, solutions, and best practices. You'll be technically proficient in machine learning and its applications; you'll demonstrate an understanding of data management and show a keen … Engineering, Architecture, and Software Development to ensure efficient operation and use of Data Science models and will facilitate the full life cycle of machine learning models from data ingestion, model development, testing, validation, deployment, to monitoring and retraining of models within different environments. If you've a strong understanding of Microsoft Azure, fluency in data science coding, and … skills Powering the business with the right tools What's involved: You'll contribute to the design and implementation of Machine Learning Engineering standards and frameworks. You'll support model development, with an emphasis on auditability, versioning, and data security. You'll implement automated data science model testing and validation. You'll assist in the optimisation of deployed 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. 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. Expertise in statistical methods More ❯

models to solve complex business problems. Collaborate with cross-functional teams to integrate ML models into production systems. Utilize PyTorch, Scikit-learn, NumPy, and Pandas for data analysis and model development. Develop and maintain APIs for model deployment and integration. Fine-tune large language models to enhance performance and accuracy. Apply deep learning architectures such as LSTMs and … Transformers to relevant projects. Stay updated with the latest advancements in generative AI and implement innovative solutions. Conduct statistical analysis to support model development and validation. Required Qualifications, Capabilities, And Skills Formal training or certification on Data engineering concepts and applied experience cProven experience in building and deploying machine learning models. Hands-on experience with PyTorch, Scikit-learn, NumPy More ❯

provides critical support for ESP to provide business actionable analysis to other departments of Pattern. KEY ACCOUNTABILITIES Create, manage, and analyze input and output data for/from executed model simulations using the WIS:dom suite of tools. Provide analysis of these inputs and outputs to the ESP team and external groups. Integrate large datasets into the modeling framework. … tasks and enhance existing workflows to improve input and output data for modeling accuracy and efficiency. Develop pipeline infrastructure between modeling tools that will reduce the manual nature of model execution in coordination with the transition to the HIVE. Work with multidisciplinary teams, including modelers, developers, analysts, GIS, and transmission analysts to align model data requirements that simulate More ❯

domain, carrying out analysis, and integrating or developing new techniques for implementation and delivery as part of our product offerings. This includes feature engineering, applying varying models, testing, and validation, and best practices for use for customers. Responsibilities: Development of predictive models using time series, geospatial and environmental sensor data. Designing scalable feature engineering and data transformation processes tailored More ❯

is greater demand and scrutiny on models than ever before in financial services. We are looking for a Risk Analyst to join the team to support with the independent validation of economic crime, climate change, Treasury valuations and predictive AI models. The growing prominence of model risk management has led Nationwide to invest in the continuous improvement of … our modelling capability, highlighting the value placed on advances in this area. As part of this investment, a fantastic opportunity has become available in Model Risk Oversight, and we are seeking a talented person to become a member of a vibrant team. Our role involves ensuring that models used for decision-making are robust, reliable and compliant with regulations. … Key responsibilities include validating model performance, checking model assumptions are appropriate and assessing the risks associated with model errors. At Nationwide we offer hybrid working wherever possible. More rewarding relationships are supported through our hybrid approach, bringing colleagues together across our UK wide estate, whilst also supporting generous access to home working. We value our time in More ❯