TL;DR

Principal Data Scientist (AI): Building and optimizing large-scale machine learning recommender systems for flagship products with an accent on prototyping, experimentation, and guiding technical strategy. Focus on solving complex ML production challenges and delivering scalable solutions at the BBC’s scale.

Location: Hybrid role; must be based in the UK (Salford, Glasgow, Newcastle, or London).

Salary: £73,000 - £83,000.

Company

A globally renowned public service broadcaster dedicated to informing, educating, and entertaining audiences through content, digital products, and innovative technology.

What you will do

  • Lead the technical direction of large-scale recommender systems used by millions of daily users.
  • Prototype, experiment, and guide technical approaches for complex ML solutions.
  • Partner with engineers, product managers, and data scientists to deploy high-impact systems.
  • Collaborate to overcome real-world production challenges in ML development.
  • Contribute to the wider Data Science community through knowledge sharing and mentorship.

Requirements

  • Must have the right to work in the UK.
  • Extensive hands-on experience in data science and machine learning.
  • Proven track record in developing and deploying recommender systems.
  • Strong proficiency in Python.
  • Ability to communicate technical concepts to both technical and non-technical stakeholders.
  • Experience working effectively within cross-functional teams.

Nice to have

  • Experience with MLOps, model deployment, versioning, and monitoring.
  • Knowledge of cloud services, specifically AWS.
  • Strong understanding of software development best practices like testing and code management.
  • Experience mentoring or supervising team members.

Culture & Benefits

  • Flexible 35-hour working week with options for hybrid working.
  • 25 days annual leave plus the option to buy 5 additional days.
  • Defined benefit pension scheme.
  • Professional development and career growth opportunities.
  • Discounts on dental, health care, and gym memberships.

Hiring process

  • Introductory call with the hiring manager regarding role background and motivations.
  • 1.5-hour panel interview featuring a technical presentation and competency-based questions.