Job Specifications
Job Description
Data Scientist
Salary: £60,000 - £85,000 depending on experience, plus bonus and benefits
Contract type: Permanent
Shift pattern: Full-time – 37.5 hours per week
Location : Hybrid / London EC2R 7HJ, Salford M50 3SP, Staines TW18 3DZ. 1 day in a office per month
Closing date: 13/02/2026
We make health happen
At Bupa, we’re not just a health insurer – we’re a health partner. With no shareholders, our focus is always on our customers. We’re here to help people live longer, healthier, happier lives – and make a better world.
Role Overview
As part of our ambitious 2027 strategy, you’ll join a growing Data Science team working at the intersection of data science, machine learning, healthcare evaluation, analytics and AI to transform healthcare.
How You’ll Help Us Make Health Happen
Leading and supporting end-to end healthcare data science projects including business case development, data processing, exploratory and statistical analyses, machine learning and model development on a diverse range of complex healthcare datasets.
Health programme evaluation including the use of clinical outcomes, health and wellbeing measures, customer experience and modelling impact on morbidity, mortality and economic measures.
Identify, evaluate, and prioritise emerging data science and AI opportunities across Bupa Health Services where advanced analytics, machine learning, or automation can drive measurable improvements in health outcomes, service delivery, and operational efficiency.
Acting as a health data SME by working closely with clinicians, operational and business managers to collaborate on the art of the possible, developing new use cases for data science and AI in healthcare and knowledge sharing across Bupa’s global businesses.
Working with multi-modal data sources such as electronic health records, wearable sensor data, imaging data to extract insights, automate processes and deliver impactful data and AI solutions.
Committing to continuous professional development, aligning learning with organisational goals and emerging trends in AI and data science.
Ensuring full compliance with all relevant regulatory frameworks and standards (e.g., GDPR, DPA) as well as proactively aligning to Bupa’s Responsible AI Framework.
Key Skills / Qualifications Needed For This Role
Extensive applied experience in data science including within healthcare or clinical settings.
Demonstrated expertise in medical statistics, epidemiology, and population health, with a proven ability to apply advanced statistical techniques to complex health datasets. The candidate should possess a deep understanding of study design, statistical modelling (e.g., survival analysis, regression techniques, longitudinal data analysis), and epidemiological methods for assessing disease patterns, risk factors, and health outcomes across populations.
Experience forecasting healthcare demand and utilisation.
Hands-on experience with Python and SQL within a cloud environment such as Snowflake, Azure and GCP.
Demonstrated knowledge and experience in delivering end-to-end AI and GenAI projects, including business case development, model building, deployment and monitoring in production environments.
A solid understanding of machine learning infrastructure and architecture, with the ability to support technical teams in developing scalable ML platforms.
Experience working in an agile environment, preferably with familiarity using Azure DevOps tools such as Boards, Repos, and Pipelines to manage workflows and collaborate effectively.
Excellent communication and stakeholder management skills, with the ability to influence and collaborate across technical and non-technical teams.
Experience in translating analytical findings into actionable insights to inform clinical decision-making, health programme development and evaluation is essential.
A naturally inquisitive and curious mindset with a strong drive to explore complex healthcare data, ask meaningful questions, and uncover hidden patterns and insights. Demonstrates a proactive approach to learning and discovery, continuously seeking to understand the 'why' behind the data and its clinical implications.
Nice to Have
Proficiency in R and Power BI
Understanding of clinical genomics analysis, including the interpretation of genomic variants in the context of disease prevention, cancer genomics, and pharmacogenomics
Experience in health economics, including the application of economic evaluation methods such as cost-effectiveness analysis, cost-utility analysis, and budget impact modelling to inform healthcare decision-making.
Clinical background or background in life science.
Analytical or data science background in health insurance.
Benefits
Our benefits are designed to make health happen for our people. Viva is our global wellbeing programme and includes all aspects of our health – from mental and physical, to financial, social and environmental wellbeing. We support flexible working and hav