Data Scientist reference: R1193268

This review offers insights into the Actuarial Data Scientist role at Bupa, designed to help potential candidates understand the opportunity and guide their career path. Bupa is a global health insurer and provider with a clear mission: helping people live longer, healthier, happier lives. This purpose-driven culture, free from shareholder demands, places customers at its core.

Key Advantages for Candidates:

• Impactful Work: You'll contribute directly to Bupa's digital and data strategy, working on innovative projects that make a tangible difference in the lives of colleagues, customers, patients, and residents.
• Career Development: The role emphasizes personal and professional growth, encouraging the development of actuarial techniques and providing opportunities to learn and evolve alongside Bupa's journey.
• Modern Technology Stack: Leverage Bupa's new data platform on Snowflake for advanced trend insights and forecasting, offering a chance to work with cutting-edge tools and technologies.
• Flexibility: Bupa offers flexible working options, including hybrid models (up to 4 days WFH) and considerations for various locations, hours, and working patterns, catering to a diverse workforce.
• Comprehensive Benefits: Enjoy a competitive salary of up to £55K per annum (dependent on experience), 25 days of holiday (increasing with service), Bupa health insurance, an enhanced pension plan, life insurance, access to gyms or discounts, and various other perks.
• Inclusive Culture: Bupa champions diversity and encourages all employees to "Be you at Bupa." They actively seek candidates from diverse backgrounds and are committed to fair treatment and reasonable adjustments for all applicants.

Key Considerations for Candidates:

• Role Responsibilities: The core of this role involves building and refining models for reserving, planning, and reporting, using statistical techniques and software. You will forecast claim inflation, detect new trends, and develop impactful time-series and other predictive models.
• Technical Skills: Strong proficiency is required in statistical modeling using tools like SAS, R, and Python. Expertise in Snowflake for data management and analysis is crucial. Experience handling large, structured, and unstructured datasets is essential.
• Data Visualization & Communication: The ability to present data effectively using tools like Power BI and Tableau, and to clearly communicate complex insights to various stakeholders across Pricing, Finance, and Healthcare Management, is vital for steering company strategy.
• Process Improvement: Opportunities exist to automate processes using Python and Power BI, and to innovate by challenging existing norms and leading best practices.
• Collaboration: You will collaborate closely with data engineers to define requirements for model builds and data feeds, and work with stakeholders across different departments.
• Industry & Actuarial Knowledge: While experience in the insurance industry and knowledge of key actuarial principles are desirable, they are not always essential, especially for candidates with a strong data science foundation and a willingness to learn.

This Actuarial Data Scientist position at Bupa presents a compelling opportunity for driven individuals passionate about data and keen to make a significant impact within a purpose-led organization. It offers a blend of challenging analytical work, continuous professional development, and a supportive, flexible working environment.