Experimentation Lead

JOB DETAILS JOB BAND: E CONTRACT TYPE: Fixed-term DEPARTMENT: Chief Operating Group / Product Group / Engineering & Data / Experimentation LOCATION: London – Salford PROPOSED SALARY RANGE: £75,000 - £85,000 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 To define and maintain how we design, conduct and analyse experiments across the BBC. This role is crucial in creating a culture of experimentation through consistent, evolving process that inform decision making. You will work with product teams across the BBC to create elegant solutions and templates that streamline operations and improve the ease to apply experimentation methodologies. • Develop an understanding of our product, operations, systems and processes by interacting with product managers, engineering and business teams. • Work with the Product, Design, Engineering and experimentation teams to improve ways to identify, prioritise, design, implement and own the backlog of experiments. • Establish experimentation standards that promote consistency and best practices across the business, and communicate these standards effectively to the broader data team. • Work with the experimentation team to develop methods and tools that increase the rigor and efficiency of our experimentation platform and analyses that are constructed using causal inference techniques. • Partner with design and product to identify key questions and opportunities, and construct pragmatic agendas to guide hypothesis-based learning strategies to build an experimentation roadmap and answer these question. • Work with the Data Platforms team to improve the processes, knowledge, and tools to support growing business demand for high-quality experimentation planning and execution. • Advocate for experimentation depth, rigor, and consistency across the data and business teams, and coach data team members on the principles of effective experimentation and inference WHY JOIN THE TEAM This is a unique opportunity to shape how the BBC learns, innovates, and makes product decisions at scale. You’ll work at the heart of a highly collaborative, mission-driven organisation, partnering with talented product, design, engineering and data teams to build an experimentation culture that impacts millions of users. If you’re passionate about using data, experimentation, and rigorous thinking to drive meaningful change, this role gives you the influence, autonomy, and scope to make a lasting mark across the entire BBC digital ecosystem. Your Key Responsibilities And Impact • Maintain a high level view of the experimentation activities across all products: You will be responsible for identifying, reviewing and communicating the key problems the business is trying to solve through experimentation. • Champion hypotheses definition and experimental design process across the product development lifecycle to capture all assumptions and decisions as hypothesis to test. • Collaborating with cross-functional teams: You will work closely with designers, product managers, data analysts, and engineers to define experiment goals, set up tracking and measurement, and interpret results. • Ensuring high-quality experiments: You will be responsible for ensuring that experiments are properly designed, executed, and analyzed, with the appropriate statistical rigor and validity. • Analyzing and interpreting results: You will be responsible for analyzing experimental results, interpreting their implications, and presenting them to stakeholders. • Communicating insights: You will be responsible for communicating insights and recommendations to stakeholders, including senior leadership, in a clear and actionable manner. • Staying up-to-date with experimentation best practices: You will be responsible for staying up-to-date with the latest experimentation best practices and tools, and sharing your knowledge with the broader team. • Driving a culture of experimentation: You will be responsible for driving a culture of experimentation, where everyone is encouraged to test assumptions and learn from their experiments. Overall, your role as an experimentation lead will be critical in helping the product teams drive growth, optimize user experiences, and achieve business objectives through data-driven experimentation. Your Skills And Experience • 7+ years experience with statistical analysis and tools like Excel, R, or Python • 5+ years experience in designing experiments, including A/B testing and randomized controlled trials, and an understanding of experimental design principles • Ability to formulate hypotheses and test them using statistical methods as well as testing tools • Excellent communication skills, both written and verbal • Problem-solving: strong problem-solving skills and ability to develop innovative solutions to complex problems • Project management: experience in project management and ability to manage multiple experiments simultaneously • Business acumen: understanding of business objectives and ability to align experimentation goals with these objectives • Attention to detail: detail-oriented with a strong focus on accuracy when analyzing data and designing experiments Essential Criteria • Advanced statistical & causal inference expertise. deeply skilled in experimental design, power analysis, causal methods, and interpreting complex data with rigor. • Strong hands-on technical capability. Fluent in Python/R, SQL, experimentation platforms, analytics tooling, and able to build or optimize experimentation workflows. • Experience scaling experimentation systems. proven ability to design and improve frameworks, templates, and automated processes that enable high-quality experimentation at scale. • Ability to diagnose and resolve technical experimentation issues. strong debugging mindset for data pipelines, tracking, measurement, instrumentation, and experiment validity threats. • Data-driven decision leadership. able to translate complex analyses into clear insights, influence technical and non-technical teams, and drive adoption of experimentation best practices. Desired But Not Required • Experience with large-scale digital media or streaming products, ideally in organisations with broad audience reach, large & complex data sets. • Familiarity with experimentation platforms such as Optimizely, Growthbook, Redshift or home-grown experimentation frameworks. • Knowledge of advanced causal inference techniques beyond standard A/B testing (e.g. difference-in-differences, synthetic controls, Bayesian experimentation). • Experience mentoring or training teams on data literacy, experimentation culture, or statistical thinking. If you can bring some of these skills and experience, along with transferable strengths, we’d love to hear from you and encourage you to apply. Before your start date, you may need to disclose any unspent convictions or police charges, in line with our Contracts of Employment policy. This allows us to discuss any support you may need and assess any risks. Failure to disclose may result in the withdrawal of your offer. Disclaimer This job description is a written statement of the essential characteristics of the job, with its principal accountabilities, incorporating a note of the skills, knowledge and experience required for a satisfactory level of performance. This is not intended to be a complete, detailed account of all aspects of the duties involved. Please note: If you were to be offered this role, the BBC will conduct Employment screening checks which include Reference checks; Eligibility to work checks; and if applicable to the role, Safeguarding and Adverse media/Social media checks. Any offer made is conditional on these checks being satisfactory. For any general queries, please contact: bbchr@bbc.co.uk Redeployment The BBC is committed to redeploying employees seeking suitable alternative employment within the BBC 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.