Senior Data Scientist

Company: carwow
Apply for the Senior Data Scientist
Location: London
Job Description:

Overview

As a Senior Data Scientist at Carwow, you will lead end-to-end ML and AI projects that fuel a large two-sided car marketplace. You’ll partner with commercial, product, marketing, and operations teams to translate business problems into production-ready models and AI solutions. Your work will span pricing, demand signals, personalised recommendations, and LLM-powered operations support, delivering measurable business impact. This role offers high ownership, cross-functional collaboration, and opportunities to shape data science standards and AI adoption at scale.

Pay / Benefits

  • Hybrid working
  • Competitive salary
  • Matched pension contributions
  • Share options
  • Vitality Private Healthcare
  • Learning and development budget

Responsibilities

  • Lead end-to-end ML/AI projects from framing to deployment, monitoring, and iteration
  • Design and deploy GenAI/LLM solutions alongside classical ML with clear value judgments
  • Drive commercial impact through models that improve marketing efficiency, pricing, or recommendations
  • Prototype and run rapid experiments with clear success metrics to decide on scale
  • Collaborate with Commercial, Marketing, Product, Finance, Engineering, and Operations to understand problems and translate findings
  • Contribute to shared best practices, documentation, and ways of working to raise DS standards and promote AI adoption

Key requirements

  • Commercial mindset and ability to tie models to revenue, efficiency, or customer outcomes
  • Strong stakeholder partnership with cross-functional teams
  • Sound judgement on tooling choices and when to apply GenAI vs classical ML
  • Bonus: marketplace or two-sided platform experience
  • Proven ML experience in Python in production, owning models post-deployment
  • Cross-functional communication
  • Strategic problem framing
  • Rigorous experimentation and metric-focused thinking
  • Python
  • SQL
  • MLOps and end-to-end model lifecycle

Posted: September 18th, 2026