Pricing Data Scientist

(Senior) Pricing Data Scientist | £80-100k + Bonus | Hybrid in London

A rare chance to build risk-based pricing from scratch, with a direct line to senior leadership.

I’m partnering with a high-growth UK home services group on a newly created, greenfield hire. They’re looking for their first Pricing Data Scientist to introduce risk-based pricing into a market where most providers still price flat.

About my client

A fast-growing UK challenger operating across home cover, renewable installations and financing. Following a recent major acquisition, they’re entering a significant growth phase with fresh investment behind it. It’s a genuine inflection point, and they want someone who’ll help shape what comes next.

Why this role stands out

• Greenfield ownership: you’ll build the capability from the ground up, with strong support but no inherited template
• Visibility: your work feeds a group-level commercial programme with a material financial outcome, and you’ll present directly to senior leadership and a non-executive director who has built risk-based pricing at scale
• Impact: the models you build will shape pricing decisions across multiple brands
• Research-friendly: the client values raw quantitative ability, rigour and curiosity over years spent in a pricing job

What you’ll be doing

• Building risk-based pricing models using property, location, appliance age and enrichment data (credit, geospatial), with sensible guardrails such as caps and collars
• Designing and running their first price elasticity tests, starting with champion/challenger and holdout tests on renewals
• Building customer lifetime value models across brands, so pricing is driven by value rather than volume alone
• Establishing monthly backtesting, version-controlled code and documented methods, so pricing stands up to external review
• Evaluating and integrating third-party data sources, working with engineers to land them cleanly in the warehouse
• Presenting findings in plain English and helping leadership make trade-offs explicitly

What my client is looking for

• A PhD or equivalent research-level experience in maths, statistics, physics, computer science or a similar quantitative discipline
• Strong grounding in GLMs, experimental design and causal inference
• Clean, reproducible Python and confident SQL, with Git as a habit
• Commercial instinct and the ability to explain complex analysis simply

Nice to have: pricing or experimentation experience (insurance, gambling, price comparison, energy, subscriptions), LTV or survival modelling, credit/property/geospatial data, Bayesian methods

The role can pay between £80-100k DOE and includes a performance bonus. The role requires 2 days a week in central London.

(Senior) Pricing Data Scientist | £80-100k + Bonus | Hybrid in London

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