11 of 11 Remote Model Validation Jobs in the North West

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 ❯

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 ❯

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 ❯

and frameworks used across the company’s data science organisation. Key Responsibilities: Design and deploy time series forecasting models with a strong focus on accuracy and scalability Improve existing model performance and drive innovation through new methodologies Develop internal ML and forecasting libraries using Python Translate product goals into technical solutions in collaboration with leadership Implement validation frameworks … unit tests, and monitoring pipelines Stay current with advances in machine learning and apply them where appropriate DevOps-first approach for model deployment Skills & Experience: Strong background in statistics, machine learning, and time series forecasting Experience with modern ML models (e.g. transformers, CNNs, attention mechanisms) Proficiency in writing production-level Python code Familiarity with CI/CD practices, testing … and model validation Confident working across teams and taking ownership of delivery Strong communication and problem-solving skills Experience in demand forecasting or operations research Familiarity with Bayesian methods, Monte Carlo simulations, or reinforcement learning Exposure to high-scale SaaS or B2C products Why Apply? Build forecasting systems powering global commercial strategies Collaborate with a world-class data More ❯

assist the ML team. Help design, implement, and refine ML algorithms and tools. Collaborate with cross-disciplinary teams to integrate ML models into game development. Conduct experiments to improve model performance. Help train, retrain, and maintain ML systems for game development. Participate in meetings to support updates and provide insights. Requirements: BSc in Computer Science, Mathematics, or related field More ❯

reports to communicate findings and predictions to stakeholders, including good presentation skills. Collaboration: Work closely with commercial, operational, and technical teams to understand business challenges and deliver actionable insights. Model Evaluation & Maintenance: Continuously monitor, validate, and refine predictive models to ensure accuracy and relevance. Essential Skills & Experience Develop and implement predictive models to forecast key metrics such as sales More ❯

will support the requirements of the business. Liaise with the IT team and data scientists to strive for greater functionality in our data systems. Establish efficient, automated processes for model development, validation, implementation and documentation. The Successful Applicant The successful Data Engineer should have: Proficiency in Big Data Modelling, ETL and Data warehousing. Proficient in SQL Snowflake Tableau More ❯

and insightful visualisations and reports to communicate findings and predictions to stakeholders. Collaboration: Work closely with commercial, operational, and technical teams to understand business challenges and deliver actionable insights. Model Evaluation & Maintenance: Continuously monitor, validate, and refine predictive models to ensure accuracy and relevance. Essential Skills & Experience: Preference for ‘R’ programming language but other machine learning languages/tools More ❯

modelling environments Supporting technical leads to independently implement changes to the SAS based Stress Testing Engines and associated analytical tools Focusing on continuous improvement through addressing of the Open Model validation actions and by identification of model performance issues, addressing oversight actions and by embedding learnings and evolving business and regulatory requirements Ensuring effective design and implementation … for obtaining insights and feedback for the management of the credit stress testing models Assisting the operational/delivery arm of the credit stress testing team in relation to model usage. We need you to have Good Knowledge of Climate risk model methodologies and stress testing frameworks across a range of Retail/Business credit portfolios with a … good understanding of model usage Strong model development experience in stress testing, ideally using SAS and R Effective Climate Risk Modelling skills across physical risk and transition risk A strong understanding of climate-related regulations and reporting standards (e.g. TCFD, ESG reporting) Excellent analytical ability to solve complex problems, with a keen attention to detail Brilliant communication skills More ❯

About the Role Location: United Kingdom, Manchester Remote vs. Office: Hybrid (Remote/Office) Company: Siemens Energy Limited Organization: Grid Technologies Business Unit: Grid Solutions Employment Type: Full-time Experience Level: Not specified A Snapshot of Your Day: As a More ❯