Why This Role Stands Out
You'll shape innovative pricing strategies and deploy machine learning models from concept to production within a highly respected financial services leader, enjoying a competitive salary range of £60k-£100k and hybrid flexibility. This role is perfect for a driven Senior Data Scientist with end-to-end ML project experience and a passion for solving real-world commercial challenges, offering significant impact and career growth. Embrace this exciting opportunity to drive business value and advance your skills.
Quick Overview
Job Description
I'm hiring a Senior Data Scientist to join a leading UK insurer's Pricing & Data Science function, working on innovative machine learning solutions that directly influence risk assessment, pricing, fraud detection, and commercial performance.
This is a role for someone who enjoys taking models from problem definition through to deployment, working with modern ML techniques and real-world commercial challenges.
1 day/week (Leicester / London / Bexhill)
£60k-£100k
What you'll be doing
- Build and deploy predictive models across pricing, claims, fraud, and risk analytics.
- Engineer new data assets and rating factors to improve pricing performance.
- Identify and leverage new data sources to drive business value.
- Partner with stakeholders across Pricing, Data Science, Analytics, and Engineering teams.
- Own ML projects end-to-end, including EDA, deployment, monitoring, and model refreshes.
What they're looking for
- Proven experience delivering ML projects from concept to deployment.
- Strong Python and SQL skills.
- Experience with Azure ML, Git, and cloud-based analytics environments.
- Strong stakeholder engagement and commercial problem-solving capability.
- Passion for applying emerging ML techniques to real business problems.
Why join?
- Work in a highly respected pricing and analytics function.
- Bonus scheme + £5k car allowance.
- Private medical cover and strong benefits package.
- Opportunity to work on innovative modelling and pricing challenges at scale.
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