Fancy working on one of the largest media datasets in the world, helping the BBC model how audiences discover, consume and engage with content?
The BBC is a major stakeholder in industry-leading audience measurement systems. Alongside this, our digital products—including iPlayer, Sounds, News and Sport—reach millions of people every week and generate billions of audience interactions.
As a Data Scientist, you will develop statistical and machine learning models that help understand audience behaviour, improve audience measurement, and support strategic decision-making across the BBC. Working with a range of data sources, from digital behavioural data to audience panels and surveys, you'll deliver robust analysis that influences how the BBC measures success and plans for the future.
WHY JOIN THE TEAM
You'll join a team of around 12 Data Scientists working on a diverse range of modelling challenges. Our work spans audience measurement, forecasting, consumer behaviour, experimentation and applied machine learning.
We work closely with data engineers, researchers, analysts and stakeholders across the BBC, giving you the opportunity to contribute to high-impact projects with visible organisational value.
You'll also be part of a wider data science community and have dedicated time to develop your technical skills, explore new approaches and contribute to best practice across the organisation.
YOUR KEY RESPONSIBILITIES AND IMPACT:
- Apply statistical and machine learning techniques to answer business questions and improve understanding of audience behaviour, combining data from multiple sources from digital activity to panel data
- Design, develop and evaluate analytical models, ranging from exploratory analyses and proof-of-concepts through to production solutions delivered in partnership with engineering teams.
- Develop reproducible analytical workflows using SQL, Python or R on our data and machine learning platform
- Develop an understanding of the BBC and wider media markets, to help position models and analysis in real terms, and communicate findings, assumptions and recommendations appropriately to non-technical stakeholders
- Keep up to date with latest development in machine learning and generative AI, promoting innovation, best practices and standards across data science work within the team
