BIT
Head of Data Science
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About the Role
BIT is in the business of developing, testing, and recommending evidence-based policy and services. We do this as rigorously as possible, typically through randomised controlled trials (RCTs) and quasi-experimental designs (QEDs). Alongside these core established methods, we are increasingly using advanced data science, machine learning, and natural language processing techniques. Recent examples include machine learning to pinpoint at-risk online gamblers for targeted support, conducting network analysis to enable anti-conflict programmes in schools, and natural language processing to understand the role of local media in communities. Crucially, we are pioneering AI-enabled methods—to ensure our research, policy, service, and product development remains rigorous, behaviourally informed, and cutting-edge.
The Head of Data Science is a critical role within our methods leadership team. You will be the technical anchor for our data science function, ensuring the highest standards of data ethics, security, quality, and technical rigour. Working closely with the Group Director of Research, the research and the product teams, you will bridge the gap between organisational strategy and technical execution, growing our data science portfolio and helping the product team interface effectively with the wider business. You will lead on technical responses for new business, oversee our data science QA processes, and mentor a talented team of data scientists to deliver on BIT’s strategy.
Crucially, you will also contribute to BIT’s AI roadmap alongside other leaders. This includes transforming internal workflows for our researchers and data scientists, embedding AI across our research processes, and building innovative, AI-enabled research capabilities—recognising that while BIT is not a pure AI product company, agentic tools open powerful new possibilities for social impact. For example, we’ve already deployed AI-driven conversational tools to conduct qualitative interviews at scale and harnessed natural language processing for thematic analysis to draw rapid, meaningful insights from vast numbers of transcripts.
Above all, BIT is a genuinely exciting place to work. Across our global offices, you’ll collaborate with world-leading behavioural scientists, policy specialists, methods experts and innovators who are passionate about leveraging data, evidence, and emerging technology to solve complex real-world challenges.
What you will be doing:
- Strategic Leadership: Working with the Group Director of Research and data scientists to design and execute a data science strategy for BIT. This includes ensuring our data science offer remains robust and cutting-edge, our specialists have the right support and development opportunities, and we recruit and retain the right talent to deliver on our research and organisational strategy.
- Business Development & Commercial Growth: Cultivating a specialised portfolio of data science projects and embedding data science into our core behavioural science client offer. You will lead the technical elements of responses and costings for new business opportunities, brainstorm data-driven project ideas with clients, and equip policy leads to pitch data science capabilities effectively.
- AI Roadmap & Innovation Leadership: Co-leading the shaping of BIT’s AI roadmap alongside other leaders. This includes the evolution of our internal ways of working and our future service offer, including embedding emerging agentic AI capabilities, ensuring all AI adoption maintains strict standards of quality and data security.
- Product Team Integration: Partnering closely with BIT’s product team (Product Lead, Lead Full Stack Developer, and Data Engineer) and Group Head of Data Engineering to bridge the gap between technical execution and organisational strategy, helping the product team interface effectively with the wider business.
- Methodological Leadership and Technical Voice: Serve as the final technical authority and expert voice on data science across the organisation, leading complex projects and overseeing the methodological quality of our machine learning, predictive modelling, and data visualisation work.
- Delivering Practical Client Solutions: Act as a primary bridge to non-technical clients—translating complex methodologies into clear, intuitive concepts, distilling technical findings into actionable recommendations, and balancing deep technical rigour with commercial awareness—effectively guiding clients, holding your ground on what is technically feasible within scope and budget, and collaborating to find practical solutions.
- Setting and Maintaining Standards: Setting, maintaining, and monitoring product and data science workflows and data ethics standards across BIT. This includes overseeing our data science and product quality-assurance (QA) processes—including rigorous code QA—and ensuring our onboarding, training materials, and methodological guidance are up to date.
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Who you are:
We are looking for a candidate with deep technical expertise and the leadership skills to guide a high-performing team.
Essential Skills & Experience:
- Advanced Data Science & Econometrics Expertise: Strong skills in the theory and application of machine learning (e.g., predictive modeling, supervised/unsupervised learning, clustering) and regression frameworks (LMs, GLMs). Deep experience working with, cleaning, and analysing large, complex datasets (such as administrative or government data).
- Programming Mastery (Python, R): Fluency in common programming and data science languages, in particular, Python and its data science ecosystem and R. Experience building scalable, reproducible data infrastructure and pipelines, writing clean, well-documented code, and overseeing team-wide version control and code quality-assurance (QA) processes.
- AI & Technical Methods Innovation: Proven experience working with cutting-edge AI methodologies, including utilising Large Language Models (LLMs) and exploring the application of agentic AI tools within a services or research context.
- Commercial Acumen & Client Management: A proven ability to build high-trust client relationships and lead technical bids, with experience developing a commercial data science offer, responding to competitive tenders, and collaborating across internal teams to design high-quality, cost-effective proposals that win work and deliver social impact. A track record of leading data science projects from scoping through to delivery—working closely with clients to frame the actual problem, and designing solutions that are adopted and demonstrably improve outcomes.
- Product & Technical Team Integration: Experience working alongside product teams (product leads, developers, and data engineers) with the ability to act as a strategic bridge, translating deep technical capabilities into organisational strategy and helping the product function interface with generalist teams.
- Familiarity with Standard Product and Data Science Tech Stack: Our product/data science defaults are: Frontend: HTML, CSS, JavaScript, Backend: Ruby, Python, JavaScript, Database: SQL.
- Leadership & People Management: Experience leading, motivating, and mentoring technical specialists, with a track record of supporting their career growth.
- Strategic Thinking & AI Roadmap Definition: Ability to contribute technical knowledge, opportunities, and constraints to a broader organisational research strategy, identify opportunities for methodological innovation, and shaping the internal and external AI roadmap.
- Communication & Data Visualisation: Exceptional ability to translate complex data science concepts, model outputs, and statistical findings into clear, accessible, and actionable insights for non-expert audiences, policymakers, and practitioners through advanced data visualization.
- Mixed Methods: Experience co-designing and working on mixed-methods projects with quantitative evaluators and/or qualitative method experts.
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Desirable Skills:
- Causal Inference & Rigorous Evaluation: A solid understanding of causality and research designs for estimating impact, including randomized controlled trials (RCTs, stepped wedge designs), quasi-experimental designs (QEDs) such as Difference-in-Differences (DiD), Regression Discontinuity Design (RDD), and Propensity Score Matching, and power calculations.
- Principles of Qualitative Methods and How These Apply in Evaluation Contexts: (e.g., implementation and process evaluation)
What we offer:
- Work with amazing clients across the private and public sectors, focused on delivering social impact across a wide range of public policy issues from energy and climate change, health and wellbeing, education, work and employment.
- The opportunity to lead and shape a key strategic area of the BIT business and scale our social impact.
- A dynamic, collaborative, and supportive work environment, with flexible working, and collaboration opportunities with the charity, Nesta (BIT’s parent organisation).
Application process
This role will be open to applications from Wednesday 22nd July 2026 12:00pm BST to Monday 3rd August 2026 12:00pm BST.
Right to work in the UK:
You will need to already have the right to work in the UK in order to be able to undertake this role. We will ask all applicants to provide evidence of their right to work during the recruitment process.
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