Lead Data Scientist - GenAI

JOB DETAILS

JOB BAND: E
CONTRACT TYPE: Permanent, Full-time  
DEPARTMENT: BBC Group Strategy and Transformation
LOCATION: Salford
PROPOSED SALARY RANGE: £80,000 - £90,000 depending on relevant skills, knowledge and experience. The expected salary range for this role reflects internal benchmarking and external market insights.

PURPOSE OF THE ROLE

The Lead Data Scientist will help the BBC make practical use of AI tools and systems to solve business problems and help our internal teams work effectively and efficiently. 

The role is in the BBC’s Generative AI Programme and will collaborate closely with project managers, data scientists, analysts, domain experts, and the BBC's technical teams. Working with Programme Leadership, the Lead Data Scientist will design and build the solutions, pipelines, models and evaluation harnesses that take AI projects from piloting through to successful handover to the business for scaling, while guiding the technical approach of the wider team and helping to shape how the Programme evaluates and adopts emerging AI capabilities responsibly. 

WHY JOIN THE TEAM

The Generative AI Programme, part of the Strategy & Transformation team, helps the BBC realise value from rapidly evolving AI capabilities in a way that is practical, responsible and aligned to the BBC’s public service mission. The team’s activities include enabling adoption of AI tools across the organisation; fostering innovation; finding opportunities to use AI to work more efficiently as an organisation, and leading the BBC's engagement on the wider AI issues that shape our operating environment.

YOUR KEY RESPONSIBILITIES AND IMPACT 

• Design and develop models, pipelines and evaluation approaches that support high-quality AI piloting and transition to successful handover to the business for scaling. 
• Lead the technical delivery of data science work across multiple innovation projects, ensuring solutions are robust, secure and aligned to clearly defined outcomes. 
• Build and refine evaluation harnesses and testing approaches that help the BBC assess performance, quality, reliability and suitability for real-world use. 
• Work closely with editorial leads, project managers, data engineers, analysts and domain experts to translate requirements into practical, well-evidenced technical solutions. 
• Guide data approaches across the team, providing leadership, challenge and support to help maintain high standards of delivery and continuous improvement. 
• Contribute to how the team adopts and stewards generative AI, ensuring work is undertaken in a way that is ethical, responsible and consistent with BBC values. 
• Help establish scalable ways of working within the team, balancing experimentation with rigour, governance and operational resilience. 

YOUR SKILLS AND EXPERIENCE

Essential criteria 

• Significant experience of developing, deploying and operationalising data science and machine learning solutions in complex organisational environments, to build reliable, well-tested pipelines, evaluation approaches and production-ready designs. 
• Experience of working effectively in multidisciplinary teams, collaborating with engineering, delivery, research and design colleagues to develop high-quality solutions. 
• Demonstrable ability to guide technical direction, influence decisions and support the development of others through constructive leadership and collaboration. 
• Sound judgement in applying data science and emerging GenAI methods responsibly, with a clear understanding of quality, security, governance and ethical considerations. 
• Strong engineering practices including security by design, proficiency in Python, experience building with Generative AI and agentic frameworks (e.g. LangChain, LangGraph, PydanticAI) and managed AI services (e.g. Bedrock, Azure), CI/CD pipelines, and demonstrable use of AI-assisted development tools to improve code quality and delivery pace. 

Desirable criteria 

• Experience working in broadcast, media, start-up or research environments. 
• Contributions to published technical documents or thought leadership in your area of expertise. 
• Experience building evaluation harnesses for generative AI systems, including defining success criteria, designing test sets, and implementing both quantitative metrics and qualitative review processes. 
• Familiarity with agentic orchestration patterns, including multi-agent architectures, tool/function calling, and memory or retrieval