About this role
Centellic empowers organisations across the legal ecosystem with indispensable data and insight to make critical decisions on growth, risk and opportunity. It serves law firms, corporate legal departments, and legal technology vendors through market-leading platforms including Law.com and Lexology, alongside flagship industry events such as Legalweek and Legal Geek . Through proprietary data, deep legal market expertise and AI-enabled technology, our platforms are embedded in client workflows. The Data Intelligence Unit (DIU) builds the proprietary data foundation that powers Centellic products and insight. We design and run research programmes, acquire and structure new data, improve the quality and accessibility of existing assets, and turn complex evidence into clear, decision-ready outputs. We are looking for a Research & Data Specialist to help close important data gaps through primary and secondary research, strengthen the quality and usability of our datasets, and produce analysis that helps colleagues and clients understand the legal market. This is a hands-on role for someone who enjoys moving between research, analysis, and data operations. Conduct primary and secondary research on topics including legal department structures and budgets, AI and legal technology, and how organisations buy and manage legal services. Plan and deliver desk research, structured data collection and research interviews, selecting appropriate sources and documenting methods and limitations. Clean, structure, reconcile and validate data from surveys, submissions, interviews, internal systems and external sources. Analyse quantitative and qualitative data to identify patterns, trends, gaps and anomalies, and test whether findings are robust. Build clear, reusable research outputs, including datasets, tables, charts, presentations and concise written summaries. Maintain research documentation, data definitions, source records and quality checks so that outputs are transparent and repeatable. Apply AI and automation to make research, validation and analysis more efficient while protecting data quality and confidentiality.