Principal Data Scientist

British Broadcasting Corporation
Glasgow
1 week ago
Create job alert

Join to apply for thePrincipal Data Scientistrole atBBC

Job Reference:21742

Package Description:

Band:D

Salary:£69,000 - £79,000 depending on relevant skills, knowledge and experience.

Contract type:Permanent

Location:Salford, Glasgow, Newcastle, London. This is a hybrid role.

We’re happy to discuss flexible working. Please indicate your choice under the flexible working question in the application.

Excellent career progression:The BBC offers great opportunities for employees to seek new challenges.

Unrivalled training and development opportunities:Our in-house Academy hosts a wide range of courses and certification.

Benefits:We offer a negotiable salary package, a flexible 35-hour working week, 25 days annual leave with the option to buy an extra 5 days, a defined pension scheme, and discounted dental, health care, and gym.

Job Introduction:

The BBC has been serving audiences online for more than 20 years. We are making the shift from being a broadcaster to becoming a service that is directly shaped by our audiences.

We are 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.

Interview Process:

  • Hiring manager introductory call covering role background and candidate motivations for applying.
  • 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. 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.

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.

Desirable Experience:

  • Experience with model lifecycle management and MLOps.
  • Good knowledge of cloud services, ideally AWS.
  • Knowledge 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!

About The BBC:

The BBC is committed to redeploying employees seeking suitable alternative employment within the BBC for different reasons.

We value diversity and are committed to being truly inclusive.

Seniority level:Mid-Senior level

Employment type:Full-time

Job function:Engineering and Information Technology

Industries:Broadcast Media Production and Distribution

#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

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.

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.

Common Pitfalls Machine Learning Job Seekers Face and How to Avoid Them

Machine learning has emerged as one of the most sought-after fields in technology, with companies across industries—from retail and healthcare to finance and manufacturing—embracing data-driven solutions at an unprecedented pace. In the UK, the demand for skilled ML professionals continues to soar, and opportunities in this domain are abundant. Yet, amid this growing market, competition for machine learning jobs can be fierce. Prospective employers set a high bar: they seek candidates with not just theoretical understanding, but also strong practical skills, business sense, and an aptitude for effective communication. Whether you’re a recent graduate, a data scientist transitioning into machine learning, or a seasoned developer pivoting your career, it’s essential to avoid common mistakes that may hinder your prospects. This blog post explores the pitfalls frequently encountered by machine learning job seekers, and offers actionable guidance on how to steer clear of them. If you’re looking for roles in this thriving sector, don’t forget to check out Machine Learning Jobs for the latest vacancies across the UK. In this article, we’ll break down these pitfalls to help you refine your approach in applications, interviews, and career development. By taking on board these insights, you can significantly enhance your employability, stand out from the competition, and secure a rewarding position in the world of machine learning.