Building ML and GLM models for deployment into live pricing, including feature engineering and trialling new modelling approaches.
Build a deep understanding of our price optimisation lifetime value function and contribute to its development.
Develop new experimental pricing approaches, exploring new optimisation approaches, model structures, and automated learning.
Work hand in hand with ML ops and engineering functions to deploy and test new approaches.
Key Skills & Experience
Essential
Track record of building, validating, and maintaining pricing models (e.g. GLMs, GAMs, tree‑based models).
Experience in developing new pricing initiatives to make use of new models or data items, challenging the established approaches.
Experience in liaising with multiple stakeholders to effectively frame problems and building solutions with effective commercial outcomes.
Proficiency in Python, SQL, Azure ML, Git, Azure Cloud Services
Strong communication skills.
Ability to work cross-functionally with Data Engineers, Data Scientists and Pricing Analysts.
Keen interest in emerging ML techniques and their commercial value.
Desirable
Insurance industry experience.
ML Ops experience.
GitHub as a code collaboration tool.
Experience in line management.
Personal Attributes
Highly technically competent mixed with broader business understanding.
Natural problem solver who loves building creative solutions to complex real-world challenges.
Ability to work independently or collaboratively as part of a team to deliver solutions to a well-defined set of requirements.
Dynamic, flexible and delivery-focused work ethic required to adapt to a fast-paced environment
Interview Process:
Recruiter screening call
1st Round - Intro call with Hiring manager
2nd Round - Case study round
What we will give you:
Benefits: in addition to a competitive salary and £5k car allowance you will also receive...
Flexible working - we champion a flexible hybrid working approach - please speak to your recruiter to discuss in more detail
Competitive bonus scheme - all colleagues are eligible for our annual 4Cs performance bonus
Physical wellbeing - as a Band 4 colleague, Hastings pay for you to receive private medical Insurance (also known as PMI). This gives you flexibility and convenience to see a specialist or consultant and allows you to decide when and
Requirements
We are Looking for an experienced Data Scientist that wants to break free of the normal and develop real innovation to the Insurance Industry!
The Data Scientist will assist in the identification and creation of cutting-edge data assets and predictive models that feed into Hastings' market-leading pricing activities. You will also be asked to use these new models and data assets to develop innovative pricing solutions.
This role is within our Retail Pricing team with a team comprising Data Scientists/Modellers as well as Analysts all working to deliver our market leading pricing strategies.
Benefits
Flexible schedulePerformance bonus
Additional Information
Job Title: Senior Data Scientist
Location: Bexhill/Leicester/London- Hybrid
Welcome to Hastings Direct
We're a digital insurance provider with ambitious plans to become the best and biggest in the UK market. We've made huge investments in our pricing and data capabilities over the past few years, along with nurturing our 4Cs culture.
We provide insurance for over four million customers, but we know there's even bigger opportunity out there - our Pricing, Data and Analytics community value curiosity, collaboration and constructive challenge.
We are always looking for new ideas and diverse perspectives to question established thinking and drive meaningful change. Great pricing is built on trust, innovation and precision, so our aim is to ensure customers receive a fair and accurate price based on their individual risk, supporting fair outcomes, while delivering sustainable and profitable growth for our company.
Pricing is more than just a number - it's a strategic capability. At the heart of Hastings is deep risk insight - continually improving how we assess, segment and price risk through data and analytics.