Gravitas Recruitment Group (Global) Ltd
Principal Pricing Data Scientist, InsurTech
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Are you excited by the opportunity to build something from the ground up?
We're looking for a Principal Pricing Data Scientist to help establish and shape pricing capability within a technology-led insurance business operating in a highly data-driven sector. This is a rare opportunity to have a significant impact, designing core pricing infrastructure and influencing analytical strategy from an early stage.
They are an established insurer with ambitious plans to re-establish itself as the number one provider within its specialist markets. Significant investment in pricing, data science, and technology is creating an exciting environment for individuals who want to make a visible commercial impact.
You'll play a key role in building foundational pricing capability, combining data science, pricing analytics, and software engineering skills to create scalable solutions that directly influence commercial outcomes.
A major focus of the role will be designing and developing a new in-house Python rating engine, alongside creating the data and modelling foundations required for long-term pricing sophistication.
This position offers the chance to work across the full pricing lifecycle, from data preparation and model development through to optimisation and deployment.
Key Responsibilities
- Build and enhance pricing data assets and analytical foundations.
- Design, develop, and maintain an in-house Python-based rating engine.
- Develop pricing models and analytical frameworks.
- Create new rating factors and conduct research and experimentation.
- Support pricing optimisation initiatives.
- Collaborate with technology, data, and business stakeholders.
- Help establish best practices for pricing analytics and model deployment.
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About You
We're interested in candidates who combine strong technical capability with commercial thinking.
Essential Skills
- Proven experience delivering pricing analyses and modelling within a personal lines insurance business (motor, home, pet, travel, or similar).
- Strong Python development skills, with experience taking analytical solutions beyond notebooks into production environments.
- Solid understanding of statistical modelling and data science principles, with the ability to explain technical concepts to non-technical stakeholders.
Desirable Experience
- Knowledge of model deployment, MLOps, or production analytics.
- Familiarity with rating engines or pricing systems.
- Experience developing customer value, behavioral, or risk models.
They welcome candidates from a variety of backgrounds and career paths. Individuals with fewer years of pricing experience will still be considered where they can demonstrate strong technical capability, particularly in Python development and the application of data science within a commercial environment.
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Please note that studying towards actuarial qualifications is not a requirement for this role. They are equally interested in candidates from actuarial, data science, analytics, and other quantitative backgrounds who can bring the right blend of technical expertise, commercial awareness, and problem-solving ability, as well as they can demonstrate the right level of expertise in both pricing and Python.
What's on Offer
- Salary up to c.£60,000.
- Private medical insurance and pension.
- Dedicated training and development; support towards qualifying as an actuary is available, if desired.
- Opportunity to influence the direction of a growing pricing function, as well as having exposure to senior stakeholders across the business.
The role is predominantly remote, with occasional travel to the London office as required. Any associated travel and accommodation costs will be fully reimbursed.
This is an opportunity to move beyond maintaining existing models and instead build the foundations of a modern pricing capability. You'll have the autonomy to influence technology choices, shape analytical approaches, and see your work directly impact business performance.
If you enjoy solving complex problems, building scalable solutions, and creating pricing capability from the ground up, we'd love to hear from you.
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