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Data Scientist @ Bupa

Nexttrain
London
5 months ago
Applications closed

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Data Scientist

Data Scientist

Data Scientist

Senior Data Scientist - Up to £150k

Senior Data Scientist

Junior/Mid/Senior Data Scientist - Hybrid, London

Job Description:

Actuarial Data Scientist
London EC2R 7HJ
Flexible / Hybrid working options (i.e up to 3 days WFH)
Permanent
Ranging £52,500 – £65,500 (Neg) + fantastic benefits (depending on experience & location).
Full time 37.5 hours

We consider all types of flexibility, including locations, hours, and working patterns. We make health happen. At Bupa, we’re passionate about technology. With colleagues, customers, patients, and residents in mind, you’ll have the opportunity to work on innovative projects and make a real impact on their lives. Right from the start, you’ll become part of our digital & data strategy, joining us on our journey and developing yourself along the way.

Role Overview:
The Actuarial Data Scientist will identify underlying trends in our insurance data using various statistical models and software. This role involves self-directed project work and collaboration with stakeholders across Pricing, Finance, and Healthcare Management.

We are seeking a talented Data Scientist to join our team and utilise our new data platform on Snowflake to drive trend insights and forecasting for BUPA.

How you’ll help us make health happen:

  1. Lead Inflation Trend Insights & Forecasting:Utilise Bupa’s cutting-edge data platform to uncover inflation trends and support inflation forecasting.
  2. Work on Claims Inflation Forecasting:Forecast expected levels of claims inflation in different areas of the business.
  3. Trend Identification:Detect new trends and changes in data to enhance forecasting accuracy.
  4. Model Building & Insights:Create impactful timeseries models (and other models as required) and deliver actionable insights to stakeholders.
  5. Identify Trends in Insurance Data:Use a range of statistical models and software (e.g., SAS, R, Python) to understand how member, provider, claim, demographic, and other external data link to our volumes and claim spend.
  6. Present Data:Use appropriate visualisation tools (e.g., PowerBI, Tableau) to present data.
  7. Communicate Insights:Effectively communicate insights to the wider business to help steer company strategy (e.g., Reserving, Planning, Pricing).

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