Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Data Scientist

Bupa
City of London
1 week ago
Create job alert
Overview

Actuarial Data scientist – London (EC2R 7HJ) or Staines (TW18 3DZ)


Flexible / Hybrid working options (i.e up to 4 days WFH)


Permanent


Salary up to £55K per annum dependent upon experience


Full time 37.5 hours


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.


We are looking for a talented Actuarial Data Scientist to join our team. In this role, you will contribute to the development of models related to reserving, planning, and reporting workstreams using statistical models and software. You will engage in self-directed project work and collaborate with stakeholders across Pricing, Finance, and Healthcare Management.


This is all about developing you, your actuarial techniques to demonstrate value from data.


Additionally, you will leverage our new data platform on Snowflake to drive trend insights and forecasting for BUPA. If you are passionate about data science and eager to make an impact, we would love to hear from you!


Responsibilities

  • Build reserving, planning and reporting models: Utilise Bupa’s cutting-edge data platform to uncover trends and support claims reserving and annual operating planning.


  • Forecast expected levels of claims inflation in different areas of the business.


  • Detect new trends and changes in data to enhance forecasting accuracy.


  • Model Building & Insights: Create impactful timeseries models (and other models as required) and deliver actionable insights to stakeholders.


  • 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.


  • Present Data: Use appropriate visualisation tools (e.g., PowerBI, Tableau) to present data.


  • Communicate Insights: Effectively communicate insights to the wider business to help steer company strategy (e.g., Reserving, Planning, Pricing, Claims Management).


  • Automate Processes: Streamline processes using Python, Power BI, and other tools.


  • Monitor Models: Ensure the reliability and performance of models through effective monitoring.


  • Handle Large Data Sets: Work with both structured and unstructured data to derive insights.


  • Collaborate with Engineers: Partner with data engineers to define requirements for model builds and data feeds.


  • Innovate & Challenge Norms: Lead best practices and challenge existing processes to drive innovation.


  • Support & Train Team: Help colleagues get the most out of our new data platform.



Key Skills / Qualifications

  • Snowflake Expertise: Advanced proficiency in using Snowflake for data management and analysis.


  • Skilled in statistical modelling and analysis using tools such as SAS, R, Python, etc.


  • Experienced in handling large datasets, both structured and unstructured.


  • Capable of identifying and analysing trends in data to support forecasting and decision-making.


  • Proficient in building and validating timeseries and other predictive models.


  • Competent in automating processes using Python, Power BI, or similar tools.


  • Adept at presenting data using visualisation tools like PowerBI, Tableau, etc.


  • Strong communication skills for effectively conveying insights to various stakeholders.


  • Proactive in challenging existing processes and driving innovation.


  • Experienced in monitoring model performance and ensuring reliability



Desirable Qualities

  • Experience or understanding of the Insurance industry.


  • Actuarial Concepts: Knowledge of key actuarial principles.


  • Transformation Experience: Background in environments undergoing data platform transformation.



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 have a range of family friendly benefits.


Joining Bupa in this role you will receive the following benefits and more:



  • 25 days holiday, increasing through length of service, with option to buy or sell


  • Bupa health insurance as a benefit in kind


  • An enhanced pension plan and life insurance


  • Onsite gyms or local discounts where no onsite gym available


  • Various other benefits and online discounts



Why Bupa?

We’re a health insurer and provider. With no shareholders, our customers are our focus. Our people are all driven by the same purpose – helping people live longer, healthier, happier lives and making a better world. We make health happen by being brave, caring and responsible in everything we do.


We encourage all our people to “Be you at Bupa”, we champion diversity, and we understand the importance of our people representing the communities and customers we serve. That’s why we especially encourage applications from people with diverse backgrounds and experiences.


Bupa is a Level 2 Disability Confident Employer. This means we aim to offer an interview/assessment to every disabled applicant who meets the minimum criteria for the role. We’ll make sure you are treated fairly and offer reasonable adjustments as part of our recruitment process to anyone that needs them.


Additional Information

Time Type: Full time


Job Area: Finance & Accounting


Locations: Angel Court, London, Staines - Willow House


#J-18808-Ljbffr

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist (Optimisation)

Data Scientist - Tax & Legal

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.