Senior Data Scientist - Retail Price Optimisation - Motor
• About Pricing: We're at the start of an exciting transformation. With bold investment in pricing, data, and technology, we're building a new Retail Price Optimisation team to redefine how we make pricing decisions. By combining advanced analytics, machine learning, rich data, and modern cloud infrastructure, we aim to unlock faster, smarter, and fairer pricing - creating real impact for both our customers and the business. About the Price Optimisation team: We're seeking bright, ambitious individuals eager to make a meaningful impact and accelerate their growth. You'll be supported by experienced leaders in retail pricing and data science who are deeply committed to your development and success. As a lean, hands-on team, we offer a unique opportunity to take on responsibility early, drive real change, and grow alongside the business. Joining us at this early stage means you'll help shape our innovation roadmap and team culture that's centered around technical excellence, commercial impact, and delivering real value to our customers. Your day to day:
- Behavioural and Profitability Models:
- Price Optimisation:
- Innovation and Advanced Analytics:
- ML Engineering Integration:
- Leadership & Mentoring:
- MSc or PhD, or equivalent experience in a quantitative field
- Deep theoretical knowledge of statistical methods and ML algorithms and their practical applications.
- Strong proficiency in SQL and Python, especially with core ML libraries (e.g. scikit-learn, XGBoost, SciPy, PyTorch)
- Extensive hands-on experience in taking advanced statistical/ML solutions from prototype to production and delivering high-impact outcomes to complex business problems
- Proactive technical leader with a strong bias for innovation and continuous improvement, driven to challenge the status quo and deliver meaningful change end-to-end
- Excellent communication and stakeholder skills, with the ability to present technical insights clearly to non-technical audiences
- Familiarity with MLOps and development best practice, including production-grade model design and deployment, version control (e.g. Git), code reviews, CI/CD pipelines, unit testing, and collaborative workflows such as Agile.
- Experience with optimisation techniques (e.g. gradient descent, Bayesian methods, Lagrangian methods etc) and their practical application
- Experience in UK General Insurance (Motor and/or Home), with a solid understanding of pricing principles and regulatory governance.
- Familiarity with pricing/modelling software: e.g. Emblem, Radar, or Earnix
- Proficiency using cloud technologies (e.g. AWS/GCP/Azure)
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