Principal Data Scientist

BBC
Glasgow
1 week ago
Create job alert

Glasgow, Salford, London, Newcastle-Upon-Tyne

Application Deadline:9 days remaining

Job Reference:21742
Band:D
Salary:£69,000 - £79,000 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:Salford, Glasgow, Newcastle, London. 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.

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 Principal Data Scientist to join the Content Discovery (Recommendations) team. The successful candidate will be a technical leader in a cross-functional team of data scientists, engineers, product managers, editorial, and UX designers, to have real impact on millions of audience members. They will apply their technical expertise to identify and implement the best solutions to 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:

  1. Hiring manager introductory call covering role background and candidate motivations for applying.
  2. 1.5 hour panel interview including a technical presentation from the candidate and role relevant competency based questions.

Main Responsibilities

As a Principal 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 do hands-on coding work to develop, deploy and iterate on recommender systems, lead architecture design, implement ideas from recent research papers, do code reviews and set best practices.

The successful candidate will also have strong interpersonal skills to lead projects involving several different teams, such as the data science & engineering, AI research, ML platform and user-facing application teams, and to effectively engage with editorial stakeholders.

Principal Data Scientists at the BBC are expected to have an impact both within their immediate team and across the wider BBC data science/AI community, shaping 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:

  • Extensive hands-on experience in data science and machine learning.
  • Strong coding skills in Python.
  • Experience developing and deploying recommender systems.
  • 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.
  • Experience with model lifecycle management and MLOps, including model deployment, versioning and monitoring.
  • Good knowledge of cloud services, ideally AWS.
  • Knowledge and understanding of best practices such as testing, code management and deployment.
  • Mentorship of other team members.

You are encouraged to apply even if you don’t meet every one of the criteria above!

You’ll find above some of the skills and experience we expect from a Principal Data Scientist. Please do not think you have to tick all boxes: you will be working in a supportive and collaborative team, where we aim to put everyone in the condition to contribute at their best and feel that their work is useful and valued. Besides, you will find great development and learning opportunities to support your professional growth.

We value diversity and are committed to be truly inclusive and a place where everyone belongs.

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 here.

Diversity matters at the BBC. We have a working environment where we value and respect every individual's unique contribution, enabling all 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.

#J-18808-Ljbffr

Related Jobs

View all jobs

Principal Data Scientist

Principal Data Scientist

Principal Data Scientist- CPG

Principal Data Scientist

Principal Data Scientist

Principal Data Scientist, Consulting

Get the latest insights and jobs direct. Sign up for our newsletter.

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 Leadership for Managers: Strategies to Motivate, Mentor, and Set Realistic Goals in Data-Driven Teams

Machine learning (ML) has become an indispensable force in the modern business world, influencing everything from targeted marketing campaigns to advanced medical diagnostics. As industries integrate predictive algorithms and data-driven decision-making into their core operations, the need for effective leadership in machine learning environments has never been greater. Whether you’re overseeing a small team of data scientists or spearheading an enterprise-scale ML project, your leadership style must accommodate rapid innovation, complex problem-solving, and diverse stakeholder expectations. This guide provides actionable insights into how you can motivate, mentor, and establish achievable goals for your machine learning teams—ensuring they thrive in data-driven environments.

Top 10 Books to Advance Your Machine Learning Career in the UK

Machine learning (ML) remains one of the fastest-growing fields within technology, reshaping industries across the UK from finance and healthcare to e-commerce, telecommunications, and beyond. With increasing demand for ML specialists, job seekers who continually update their knowledge and skills hold a significant advantage. In this article, we've curated ten essential books every machine learning professional or aspiring ML engineer in the UK should read. Covering foundational theory, practical implementations, advanced techniques, and industry trends, these resources will equip you to excel in your machine learning career.

Navigating Machine Learning Career Fairs Like a Pro: Preparing Your Pitch, Questions to Ask, and Follow-Up Strategies to Stand Out

Machine learning (ML) has swiftly become one of the most in-demand skill areas across industries, with companies leveraging predictive models and data-driven insights to solve challenges in healthcare, finance, retail, manufacturing, and beyond. Whether you’re an early-career data scientist aiming to break into ML, a seasoned engineer branching into deep learning, or a product manager exploring AI-driven solutions, machine learning career fairs offer a powerful route to connect with prospective employers face-to-face. Attending these events can help you: Network with hiring managers and technical leads who make direct recruitment decisions. Gain insider insights on the latest ML trends and tools. Learn about emerging job roles and new industry verticals adopting machine learning. Showcase your interpersonal and communication skills, both of which are increasingly important in collaborative AI/ML environments. However, with many applicants vying for attention in a bustling hall, standing out isn’t always easy. In this detailed guide, we’ll walk you through how to prepare meticulously, pitch yourself confidently, ask relevant questions, and follow up effectively to land the machine learning opportunity that aligns with your ambitions.