Salary: £90,000 - 90,000 per year Requirements: Strong experience in machine learning, statistical modelling, or pricing/propensity modelling Proven track record of delivering models that go into production and stay there Experience working in commercial environments where data drives decisions Strong Python (or R) experience across modern data science tooling Familiarity with MLOps, model monitoring, and deployment pipelines Ability to communicate complex outputs clearly to non-technical stakeholders Responsibilities: Building and deploying machine learning models into production environments Designing decisioning systems that optimise pricing, channel selection, and asset performance Developing explainable models (SHAP, LIME, feature importance) that drive user trust Creating frameworks to measure real-world impact and model effectiveness Working with large, complex datasets across multiple markets Collaborating with product and engineering teams to embed models into live systems Technologies: AI Machine Learning Python More: We are a market-leading SaaS organization operating at scale within the automotive ecosystem, building the intelligence layer that drives real-world commercial decisions across Europe. We are investing heavily in data and AI to power a next-generation decisioning platform that helps enterprise clients make high-value pricing, trading, and operational decisions across thousands of assets, in real time. This role is hybrid, requiring two days onsite in Manchester, and offers a competitive salary of up to £90,000 plus a bonus. last updated 17 week of 2026