Senior Data Scientist - GenAI

JOB DETAILS

JOB BAND: D
CONTRACT TYPE: Permanent, Full-time  
DEPARTMENT: BBC Group Strategy and Transformation
LOCATION: Salford
PROPOSED SALARY RANGE: £60,000 - £70,000 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 Senior 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. The Senior Data Scientist will help evaluate emerging AI tools, assess whether domain data is fit for purpose, design and pilot solutions to clearly defined problems, and build the testing methods that show what works and where the limits are; working in ways that are responsible, evidence-led and aligned with the BBC's values. 

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 

• Support the evaluation of new AI tooling, including agentic tooling, helping to assess performance, reliability and practical value in BBC use cases. 
• Design and develop approaches, pilots and solutions that address clearly defined domain problems using generative AI, agentic and automation techniques. 
• Build evaluation methods and testing approaches that help BBC teams understand the efficacy, limitations and risks of emerging tools and solutions. 
• Work closely with domain experts, data engineers, analysts, researchers, designers and delivery colleagues to translate requirements into practical, well-evidenced data solutions. 
• Contribute to the development of high-quality, secure and resilient data science assets that support delivery of pilots as well as more scalable implementation where appropriate. 
• Present findings, trade-offs and recommendations clearly to a range of stakeholders, helping to inform decisions on tool adoption and solution design. 
• Ensure work is delivered in line with the BBC’s organisational values, security requirements and responsible approach to AI innovation. 

YOUR SKILLS AND EXPERIENCE

Essential criteria 

• Experience of developing and applying data science or GenAI approaches to practical business, operational or user problems, working collaboratively in multidisciplinary teams and with the discipline to produce reliable, well-tested code. 
• Strong analytical capability, including experience of evaluating models, tools or experiments and drawing clear, evidence-based conclusions. 
• Ability to communicate findings, limitations and trade-offs clearly to both technical and non-technical stakeholders. 
• Good judgement in applying data science methods responsibly, with an understanding of quality, governance, security and ethical considerations. 
• Strong engineering practices including writing clean, well-tested and maintainable code, proficiency in Python, 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. 
• A strong academic background or research credentials in data science, machine learning or a related discipline. 
• Experience building with Generative AI frameworks (e.g. LangChain, LangGraph, PydanticAI) and managed AI services (e.g. Bedrock, Azure). 
• Familiarity with agentic orchestration patterns, including multi-agent architectures, tool/function calling, and memory or retrieval augmentation. 
• Familiarity with enterprise automation toolsets (e.g. Microsoft Power Platform, Copilot Studio) and an understanding of how they complement bespoke AI solutions in large organisations.