Pricing Data Scientist

Oliver Bernard; Greater London; Hybrid; GBP 80,000 - 100,000; Full time

Benefits offered by this job

Performance bonus

Hybrid work in London

Job summary

Oliver Bernard partners with a fast-growing UK home services group to hire their first Pricing Data Scientist. The role is greenfield with ownership and high visibility across multiple brands, reporting to senior leadership.

You will design price elasticity tests, develop LTV models, integrate third-party data, and establish backtesting with version-controlled code. Requires PhD-level quantitative background and strong Python/SQL skills, with hybrid work in London.

Qualifications

• PhD or equivalent in a quantitative field.
• Strong grounding in GLMs, experimental design and causal inference.
• Proficient Python and SQL with Git versioning.
• Commercial mindset and the ability to explain analyses clearly.

Responsibilities

• Building risk-based pricing models using property, location, appliance age and enrichment data (credit, geospatial).
• Designing and running price-elasticity tests (champion/challenger, holdout).
• Building customer lifetime value models across brands to price by value.
• Establishing monthly backtesting, version-controlled code and documented methods.

Skills

Pricing models

GLMs

Causal inference

Python

SQL

Git

Education

PhD in a quantitative field

Tools

Pricing platforms

Job description

(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