76 to 100 of 145 Model Validation Jobs in England

key contributor to our forward looking research roadmap, including the build out of new systematic franchises in nature, biodiversity, adjacent sustainability thematics and beyond. YOUR ROLE 1) Quantitative Research & Model Development Design innovative new quantitative models and metrics, extend, and maintain quantitative models, metrics and investment frameworks, with rigorous back‐testing, scenario design, and attribution . Integrate new indicators … and alternative datasets; formalise feature engineering and signal decay/robustness analysis; implement model risk controls , documentation, and reproducibility. Scale and commercialise proprietary metrics for investment use‐cases and new revenue lines (e.g., indices, APIs/subscriptions, data products). 2) Data Operations & Quality Control (Automation‐First) Work with systematic team and IT to automate ingestion, validation, and … lineage/audit trails ; support data procurement and budgeting. 3) Platform Development & Process Management Co-develop with systematic team and IT a scalable data/quant architecture (data pipelines, model services, APIs) and embed SRE practices (observability, resilience, cost efficiency). Lead automation of portfolio alignment and sustainability reporting ; maintain production health, troubleshoot incidents, and drive continuous improvement. More ❯

Join us as a Model Risk Data Scientist If you have experience building and validating machine learning models, this is a fantastic opportunity join our innovative, vibrant team in our Risk function You'll be performing technical reviews and oversight of models used in the bank, and working with model development teams to continually drive up the value … generated by data-driven modelling What you'll do This Model Risk Data Scientist role will see you reviewing and independently validating assigned models in accordance with the bank's policies and model standards. You'll communicate your findings and recommendations to stakeholders and advise on how model risk can be reduced or mitigated. As well as … this, you'll be developing solutions for automating validation activities while understanding model and data usage, quality and interdependencies across the bank. Your role will also involve: Developing the team's analytics codebase, adding functionality, fixing issues and testing code Support the development of a validation framework for Gen AI models across the bank Reviewing your colleagues More ❯

aligning priorities to measurable business outcomes and clear benefits tracking Understand and communicate core AI technologies keeping abreast of latest changes and innovations Work with data teams to validate model outputs, data quality and performance metrics Ability to identify opportunities for automation and AI driven innovation within existing systems and processes Strong understanding of AI technologies and data lifecycle More ❯

Newcastle or Sheffield , whichever you prefer. We also have all the tools and tech we need to enable our people to work and collaborate flexibly. We work a hybrid model - you'll be in the office about 60% of the time, and 40% home working. We offer competitive pay of up to £99,836. You'll also get a More ❯

data (small-scale and large datasets). Contribute to product development through applied research and quantitative analysis. Perform statistical and coding-based analysis (Python, R, SQL). Support calibration model training and validation for sensor systems. Collaborate across disciplines to develop and deploy new sensing and data technologies. Document research findings and present results to technical and non More ❯

data (small-scale and large datasets). Contribute to product development through applied research and quantitative analysis. Perform statistical and coding-based analysis (Python, R, SQL). Support calibration model training and validation for sensor systems. Collaborate across disciplines to develop and deploy new sensing and data technologies. Document research findings and present results to technical and non More ❯

secure, and reproducible deployment of ML models in production and research environments. You’ll collaborate closely with AI Scientists, Data Engineers, and DevSecOps teams , building automation pipelines that accelerate model development and deployment across distributed, cloud-native systems. Key Responsibilities Design, implement, and maintain end-to-end MLOps pipelines for model training, validation, deployment, and monitoring. Develop … toolchains (GitHub Actions, Jenkins, Argo, etc.). Manage scalable cloud-based compute environments (Oracle Cloud, AWS, or GCP) for AI workloads and data processing. Build and maintain feature stores, model registries, and versioning systems to ensure traceability and reproducibility. Implement data ingestion and pre-processing pipelines to support ML and bioinformatics workloads. Collaborate with security and DevSecOps teams to … enforce best practices in access control, compliance, and governance . Support AI/ML researchers in model experimentation and infrastructure optimization. Monitor model and system performance, implement drift detection, and refine automated retraining pipelines. Contribute to the development of a modular, reusable ML platform architecture supporting multi-modal data (genomic, clinical, imaging, etc.). Essential Skills and Experience More ❯

secure, and reproducible deployment of ML models in production and research environments. You’ll collaborate closely with AI Scientists, Data Engineers, and DevSecOps teams , building automation pipelines that accelerate model development and deployment across distributed, cloud-native systems. Key Responsibilities Design, implement, and maintain end-to-end MLOps pipelines for model training, validation, deployment, and monitoring. Develop … toolchains (GitHub Actions, Jenkins, Argo, etc.). Manage scalable cloud-based compute environments (Oracle Cloud, AWS, or GCP) for AI workloads and data processing. Build and maintain feature stores, model registries, and versioning systems to ensure traceability and reproducibility. Implement data ingestion and pre-processing pipelines to support ML and bioinformatics workloads. Collaborate with security and DevSecOps teams to … enforce best practices in access control, compliance, and governance . Support AI/ML researchers in model experimentation and infrastructure optimization. Monitor model and system performance, implement drift detection, and refine automated retraining pipelines. Contribute to the development of a modular, reusable ML platform architecture supporting multi-modal data (genomic, clinical, imaging, etc.). Essential Skills and Experience More ❯

role centers on evaluating analytical workflows, modeling standards, experimentation culture, and applied business impact . This position is ideal for someone with a strong background in applied data science, model lifecycle design, and organizational data maturity — capable of analyzing current practices and defining what “best-in-class” looks like for scalable, responsible, and high-impact data science operations. Key … Responsibilities • Practice Maturity Assessment: Evaluate current data science processes, tools, and team structures to determine capability strengths, weaknesses, and improvement areas. • Framework Design: Develop and apply a structured maturity model to assess how data science work is conceived, executed, validated, and scaled. • Model Lifecycle Review: Assess practices across data preparation, feature engineering, model development, validation, monitoring … . • Collaboration & Alignment: Work with AI and Data & AI Architects to connect findings from people, platform, and practice assessments into a unified capability map. • Gap Identification: Identify gaps in model governance, documentation, and model-to-business translation and recommend actionable improvement pathways. • Reporting & Advisory: Produce detailed reports summarizing data science maturity, practice gaps, and recommendations for scaling responsibly More ❯

role centers on evaluating analytical workflows, modeling standards, experimentation culture, and applied business impact . This position is ideal for someone with a strong background in applied data science, model lifecycle design, and organizational data maturity — capable of analyzing current practices and defining what “best-in-class” looks like for scalable, responsible, and high-impact data science operations. Key … Responsibilities • Practice Maturity Assessment: Evaluate current data science processes, tools, and team structures to determine capability strengths, weaknesses, and improvement areas. • Framework Design: Develop and apply a structured maturity model to assess how data science work is conceived, executed, validated, and scaled. • Model Lifecycle Review: Assess practices across data preparation, feature engineering, model development, validation, monitoring … . • Collaboration & Alignment: Work with AI and Data & AI Architects to connect findings from people, platform, and practice assessments into a unified capability map. • Gap Identification: Identify gaps in model governance, documentation, and model-to-business translation and recommend actionable improvement pathways. • Reporting & Advisory: Produce detailed reports summarizing data science maturity, practice gaps, and recommendations for scaling responsibly More ❯

Bespak are looking for a Model-Based Systems Engineer on a permanent contract for the Kings Lynn site, PE30 2JJ. The salary range for this new position within the business is between £53k and £60k. Our generous benefits package includes 28 days leave plus bank holidays, 8% company pension contribution to employees 3%, onsite parking and medical/dental … flexibility in this onsite position within the needs of the business. Once you click apply, you will be redirected to our company website to make your application. As a Model-Based Systems Engineer, you will support the implementation of MBSE and in silico practices across the product lifecycle. Your primary responsibility will be working with senior engineers to develop … consistent with product evolution. We offer a Relocation Package for anyone looking to move into the area and can offer skilled worker visa sponsorship to eligible candidates. As a Model-Based Systems Engineer your duties will include: Developing and maintaining structured SysML system models. Supporting model traceability across the product lifecycle. Preparing and running FEA and CFD simulations. More ❯

Bespak are looking for a Model-Based Systems Engineer on a permanent contract for the Kings Lynn site, PE30 2JJ. The salary range for this new position within the business is between £53k and £60k. Our generous benefits package includes 28 days leave plus bank holidays, 8% company pension contribution to employees 3%, onsite parking and medical/dental … flexibility in this onsite position within the needs of the business. Once you click apply, you will be redirected to our company website to make your application. As a Model-Based Systems Engineer, you will support the implementation of MBSE and in silico practices across the product lifecycle. Your primary responsibility will be working with senior engineers to develop … consistent with product evolution. We offer a Relocation Package for anyone looking to move into the area and can offer skilled worker visa sponsorship to eligible candidates. As a Model-Based Systems Engineer your duties will include: Developing and maintaining structured SysML system models. Supporting model traceability across the product lifecycle. Preparing and running FEA and CFD simulations. More ❯

Bespak are looking for a Model-Based Systems Engineer on a permanent contract for the Kings Lynn site, PE30 2JJ. The salary range for this new position within the business is between £53k and £60k. Our generous benefits package includes 28 days leave plus bank holidays, 8% company pension contribution to employees 3%, onsite parking and medical/dental … flexibility in this onsite position within the needs of the business. Once you click apply, you will be redirected to our company website to make your application. As a Model-Based Systems Engineer, you will support the implementation of MBSE and in silico practices across the product lifecycle. Your primary responsibility will be working with senior engineers to develop … consistent with product evolution. We offer a Relocation Package for anyone looking to move into the area and can offer skilled worker visa sponsorship to eligible candidates. As a Model-Based Systems Engineer your duties will include: Developing and maintaining structured SysML system models. Supporting model traceability across the product lifecycle. Preparing and running FEA and CFD simulations. More ❯

and preprocess structured and unstructured data from multiple internal and external sources. Perform exploratory data analysis (EDA) to identify trends, patterns, and anomalies. Design and implement data pipelines for model-ready datasets in collaboration with data engineering teams. Apply feature engineering and selection techniques to improve model accuracy and interpretability. Develop and validate machine learning and statistical models … models using appropriate metrics and perform hyperparameter tuning for optimal performance. Convert proof-of-concept models into production-grade pipelines in collaboration with MLOps and engineering teams. Required: Translate model outcomes into actionable insights through clear storytelling and visualizations. Build dashboards and reports using Power BI, Tableau, or Python-based visualization tools. Communicate findings to both technical and non … Partner with business analysts, architects, and domain experts to define use cases and success metrics. Contribute to the enterprise AI roadmap, bringing thought leadership on analytical methodologies. Document methodologies, model logic, and validation results for audit and reproducibility. Participate in Agile ceremonies, sprint planning, and client showcases. If you'd like to discuss this data scientist role in More ❯

part of a fast-paced, agile development team Identify and prioritize opportunities to rapidly deliver new capabilities Build and maintain robust MLOps pipelines to support scalable, reproducible, and automated model development, deployment, and monitoring Leverage tools such as Airflow for workflow orchestration and MLflow for experiment tracking, model registry, and lifecycle management, ensuring strong CI/CD practices … and model governance Essential Skills Bachelor’s degree in science, engineering, mathematics or computer science (2:1 minimum) Strong python development skills Practical experience in the development of machine learning models and/or deep learning to solve complex science and engineering problems Experience with MLOps tools and practices, including Airflow, MLflow, and containerization (e.g., Docker) A passion for … innovation through collaboration Natural problem-solver with a desire to learn Organised and self-motivated Desired Skills Master’s degree in machine learning, mathematics or statistics Understanding of probabilistic model development Experience of Bayesian modelling Good understanding of software design principles and best practices Good knowledge of at least one object-oriented language Familiarity with cloud platforms (e.g., Azure More ❯

part of a fast-paced, agile development team Identify and prioritize opportunities to rapidly deliver new capabilities Build and maintain robust MLOps pipelines to support scalable, reproducible, and automated model development, deployment, and monitoring Leverage tools such as Airflow for workflow orchestration and MLflow for experiment tracking, model registry, and lifecycle management, ensuring strong CI/CD practices … and model governance Essential Skills Bachelor’s degree in science, engineering, mathematics or computer science (2:1 minimum) Strong python development skills Practical experience in the development of machine learning models and/or deep learning to solve complex science and engineering problems Experience with MLOps tools and practices, including Airflow, MLflow, and containerization (e.g., Docker) A passion for … innovation through collaboration Natural problem-solver with a desire to learn Organised and self-motivated Desired Skills Master’s degree in machine learning, mathematics or statistics Understanding of probabilistic model development Experience of Bayesian modelling Good understanding of software design principles and best practices Good knowledge of at least one object-oriented language Familiarity with cloud platforms (e.g., Azure More ❯

part of a fast-paced, agile development team Identify and prioritize opportunities to rapidly deliver new capabilities Build and maintain robust MLOps pipelines to support scalable, reproducible, and automated model development, deployment, and monitoring Leverage tools such as Airflow for workflow orchestration and MLflow for experiment tracking, model registry, and lifecycle management, ensuring strong CI/CD practices … and model governance Essential Skills Bachelor’s degree in science, engineering, mathematics or computer science (2:1 minimum) Strong python development skills Practical experience in the development of machine learning models and/or deep learning to solve complex science and engineering problems Experience with MLOps tools and practices, including Airflow, MLflow, and containerization (e.g., Docker) A passion for … innovation through collaboration Natural problem-solver with a desire to learn Organised and self-motivated Desired Skills Master’s degree in machine learning, mathematics or statistics Understanding of probabilistic model development Experience of Bayesian modelling Good understanding of software design principles and best practices Good knowledge of at least one object-oriented language Familiarity with cloud platforms (e.g., Azure More ❯

part of a fast-paced, agile development team Identify and prioritize opportunities to rapidly deliver new capabilities Build and maintain robust MLOps pipelines to support scalable, reproducible, and automated model development, deployment, and monitoring Leverage tools such as Airflow for workflow orchestration and MLflow for experiment tracking, model registry, and lifecycle management, ensuring strong CI/CD practices … and model governance Essential Skills Bachelor’s degree in science, engineering, mathematics or computer science (2:1 minimum) Strong python development skills Practical experience in the development of machine learning models and/or deep learning to solve complex science and engineering problems Experience with MLOps tools and practices, including Airflow, MLflow, and containerization (e.g., Docker) A passion for … innovation through collaboration Natural problem-solver with a desire to learn Organised and self-motivated Desired Skills Master’s degree in machine learning, mathematics or statistics Understanding of probabilistic model development Experience of Bayesian modelling Good understanding of software design principles and best practices Good knowledge of at least one object-oriented language Familiarity with cloud platforms (e.g., Azure More ❯

stores using Python, Java, or Node.js backends. + Collaborate with architects to define scalable and secure AI service architectures. Required Experience/Skills: Implementing AI/ML pipelines for model training, validation, and deployment (using tools such as MLflow, Vertex AI, or Azure ML). Manage model evaluation, drift monitoring, and continuous improvement processes. Optimize inference performance … and cost (e.g., model compression, quantization, API optimization). Ensure compliance with AI ethics, security, and governance standards. Prepare and curate training datasets (structured/unstructured text, images, code). Apply data preprocessing, tokenization, and embedding generation techniques. Work with vector databases (Pinecone, Weaviate, FAISS, Chroma) for semantic retrieval use cases. Partner with business stakeholders to identify and shape More ❯

stores using Python, Java, or Node.js backends. + Collaborate with architects to define scalable and secure AI service architectures. Required Experience/Skills: Implementing AI/ML pipelines for model training, validation, and deployment (using tools such as MLflow, Vertex AI, or Azure ML). Manage model evaluation, drift monitoring, and continuous improvement processes. Optimize inference performance … and cost (e.g., model compression, quantization, API optimization). Ensure compliance with AI ethics, security, and governance standards. Prepare and curate training datasets (structured/unstructured text, images, code). Apply data preprocessing, tokenization, and embedding generation techniques. Work with vector databases (Pinecone, Weaviate, FAISS, Chroma) for semantic retrieval use cases. Partner with business stakeholders to identify and shape More ❯

Perform exploratory data analysis (EDA) to uncover trends and anomalies Design and implement data pipelines in collaboration with data engineering teams Apply feature engineering and selection techniques to enhance model performance Build and validate ML models for prediction, classification, clustering, and optimization Use libraries such as Scikit-learn, TensorFlow, and PyTorch for supervised and unsupervised learning Implement NLP, time … and machine learning Strong Python skills and familiarity with ML libraries (Scikit-learn, TensorFlow, PyTorch) Experience with data visualization tools (Power BI, Tableau, Matplotlib, Seaborn) Ability to translate complex model outputs into actionable business insights Excellent communication skills with both technical and non-technical audiences Familiarity with Agile methodologies and cross-functional collaboration Background in banking or financial services More ❯

Perform exploratory data analysis (EDA) to uncover trends and anomalies Design and implement data pipelines in collaboration with data engineering teams Apply feature engineering and selection techniques to enhance model performance Build and validate ML models for prediction, classification, clustering, and optimization Use libraries such as Scikit-learn, TensorFlow, and PyTorch for supervised and unsupervised learning Implement NLP, time … and machine learning Strong Python skills and familiarity with ML libraries (Scikit-learn, TensorFlow, PyTorch) Experience with data visualization tools (Power BI, Tableau, Matplotlib, Seaborn) Ability to translate complex model outputs into actionable business insights Excellent communication skills with both technical and non-technical audiences Familiarity with Agile methodologies and cross-functional collaboration Background in banking or financial services More ❯

Perform exploratory data analysis (EDA) to uncover trends and anomalies Design and implement data pipelines in collaboration with data engineering teams Apply feature engineering and selection techniques to enhance model performance Build and validate ML models for prediction, classification, clustering, and optimization Use libraries such as Scikit-learn, TensorFlow, and PyTorch for supervised and unsupervised learning Implement NLP, time … and machine learning Strong Python skills and familiarity with ML libraries (Scikit-learn, TensorFlow, PyTorch) Experience with data visualization tools (Power BI, Tableau, Matplotlib, Seaborn) Ability to translate complex model outputs into actionable business insights Excellent communication skills with both technical and non-technical audiences Familiarity with Agile methodologies and cross-functional collaboration Background in banking or financial services More ❯

validate and deploy machine learning models to meet challenging customer requirements. Key Responsibilities Develop and train neural network models using frameworks such as PyTorch and TensorFlow Select and adapt model architectures to meet specific project requirements Build, curate, and manage training datasets, including data augmentation, feature extraction, and labelling Conduct model training, validation, and performance optimisation Collaborate … in Python and C/C++ Experience with neural network architectures including RNNs, transformers, and vector quantisation In-depth knowledge of machine learning architectures and training algorithms Experience in model training, quantisation, and conversion for inference Hands-on experience with data preparation, augmentation, and feature extraction Excellent communication and technical writing skills UK national, eligible for security clearance Due More ❯

validate and deploy machine learning models to meet challenging customer requirements. Key Responsibilities Develop and train neural network models using frameworks such as PyTorch and TensorFlow Select and adapt model architectures to meet specific project requirements Build, curate, and manage training datasets, including data augmentation, feature extraction, and labelling Conduct model training, validation, and performance optimisation Collaborate … in Python and C/C++ Experience with neural network architectures including RNNs, transformers, and vector quantisation In-depth knowledge of machine learning architectures and training algorithms Experience in model training, quantisation, and conversion for inference Hands-on experience with data preparation, augmentation, and feature extraction Excellent communication and technical writing skills UK national, eligible for security clearance Due More ❯