Data Scientist

Job Band

Job Reference: 21051
Band: C
Salary: up to £49,500 depending on relevant skills, knowledge and experience. The expected salary range for this role reflects internal benchmarking and external market insights.
Contract type: Permanent
Location: Newcastle, Salford, Glasgow. This is a hybrid role, and the successful candidate will balance office working with home working.

We’re happy to discuss flexible working. Please indicate your choice under the flexible working question in the application. There is no obligation to raise this at the application stage but if you wish to do so, you are welcome to. Flexible working will be part of the discussion at offer stage.

Excellent career progression – the BBC offers great opportunities for employees to seek new challenges and work in different areas of the organisation.
Unrivalled training and development opportunities – our in-house Academy hosts a wide range of internal and external courses and certification.
Benefits - We offer a negotiable salary package, a flexible 35-hour working week for work-life balance and 25 days annual leave with the option to buy an extra 5 days, a defined pension scheme and discounted dental, health care and gym. You can find out more about working at the BBC by selecting this link to our candidate pack.
If you need to discuss adjustments or access requirements for the interview process, please contact the k. For any general queries, please contact: k.

Introduction

The BBC has been serving audiences online for more than 20 years. Across key products including BBC iPlayer, News, Sport, Weather and Sounds, we entertain, educate and inform audiences in their millions every day. 

But behind the scenes we have work to do. We are making the shift from being a broadcaster that speaks to our audiences to becoming a service that is directly shaped by them and designed around their wants and needs. We are creating personalised content, products and services that bring the right content, to the right people, at the right time: a personalised BBC. This will be our greatest leap since iPlayer, and that’s why it’s right at the top of our agenda. 

At the BBC we see data science as fundamental on that journey. We use data and machine learning to enrich our content, improve journalist workflows and power personalised experiences for millions of audience members.

To help drive this effort, we’re looking for a Data Scientist to join the Content Discovery (Recommendations) team. The successful candidate will have the opportunity to have real impact on millions of audience members, by applying their technical expertise build recommender systems able to provide our audiences with the most relevant and engaging content at the right place and the right time – in other words, to build the future of personalisation at the BBC. 

Interview process:

There is a 2-stage process:
• Hiring manager introductory call covering role background and candidate motivations for applying (external applicants only).
• 1.5 hour panel interview including a technical presentation from the candidate and role relevant competency based questions. 

Responsibilities

As a Data Scientist, you will work hands-on to deliver value to BBC audiences by developing data science products at scale. We are looking for ‘T-shaped’ individuals, combining a breadth of knowledge with deep specialism in one or two areas.

You will be a contributor in a cross-functional team to build machine learning products to recommender systems across the BBC alongside product managers, software engineers, editorial, and delivery managers. 

Data Scientists at the BBC are expected to have an impact both within their immediate team and across the wider BBC data science community, helping shape technical direction, culture and ways of working. We’d love to see enthusiasm about sharing your knowledge and guiding others.

Are you the right candidate

Key criteria: 

• Understanding and/or hands-on experience of data science techniques and machine learning algorithms.
• Strong coding skills in Python. 
• Proven track record contributing to technical machine learning projects.
• Ability to clearly communicate to both technical and non-technical audiences.
• Ability to work effectively in a cross-functional team.

Desirable experience: 

• Experience working on ML projects from inception to delivery, working with engineers to put models into production.
• Theoretical understanding of and/or hands-on experience in recommender systems.
• Cloud services, ideally AWS.
• MLOps, e.g. model deployment, versioning and monitoring.
• Knowledge and understanding of best practices such as testing, code management and deployment.

About the BBC

The BBC is committed to redeploying employees seeking suitable alternative employment within the BBC for different reasons and they will be given priority consideration ahead of other applicants. Priority consideration means for those employees seeking redeployment their application will be considered alongside anyone else at risk of redundancy, prior to any individuals being considered who are not at risk.

We don’t focus simply on what we do – we also care how we do it. Our values and the way we behave are important to us. Please make sure you’ve read about our values and behaviours .

Diversity matters at the BBC. We have a working environment where we value and respect every individual's unique contribution, enabling all of our employees to thrive and achieve their full potential.

We want to attract the broadest range of talented people to be part of the BBC – whether that’s to contribute to our programming or our wide range of non-production roles. The more diverse our workforce, the better able we are to respond to and reflect our audiences in all their diversity.

We are committed to equality of opportunity and welcome applications from individuals, regardless of age, gender, ethnicity, disability, sexual orientation, gender identity, socio-economic background, religion and/or belief. We will consider flexible working requests for all roles, unless operational requirements prevent otherwise.