Rhea Soni joined the University Commercialisation and Innovation (UCI) Policy Evidence Unit as a Policy Data Scientist. UCI supports governments, funding agencies and universities to strengthen the contribution of higher education to innovation and economic growth by improving the evidence base, datasets and analytical tools underpinning commercialisation and innovation policy.

In her role, Rhea works across a range of data-driven projects focused on university innovation and knowledge exchange. She is leading the development of a UK Spinout Register, integrating data from HESA, Companies House and the Office for National Statistics to create a unified dataset for analysing spinout activity and institutional performance over time. She also contributes to the development of a national UK Patent Register in collaboration with UKRI, Research England and the European Patent Office, transforming fragmented intellectual property data into structured, policy-relevant insights. Her work spans large-scale data wrangling, entity resolution, statistical modelling and the development of analytical tools and dashboards to support evidence-based policymaking. She has also worked with the UK Foreign, Commonwealth & Development Office, applying data science methods to analyse geopolitical trends in emerging technologies and advise foreign and national policy strategy to stakeholders. 

Rhea has experience delivering end-to-end data science projects in policy contexts, from scoping research questions and building data pipelines to applying advanced statistical and machine learning methods and translating findings into actionable insights for stakeholders. She has experience across government, research and international organisations, and is particularly interested in strengthening evidence-based policymaking. Prior to joining UCI, she worked at the London School of Economics Research and Innovation unit, where she developed AI-enabled tools for citizen engagement and deployed data pipelines for public sector applications, including projects with NHS England. She has also worked with the UK Foreign, Commonwealth & Development Office, applying data science methods to analyse geopolitical trends in emerging technologies and inform policy strategy.

By training, Rhea holds a Master of Public Administration in Data Science for Public Policy from the London School of Economics, where she specialised in quantitative methods, machine learning and applied economics. She also holds a Bachelor’s degree in Information and Technology. Her skillset spans statistical modelling, data engineering and visualisation, with experience using Python, R and SQL to work with large-scale administrative and survey datasets in policy environments.  Her skillset spans statistical modelling, data engineering and visualisation, with experience using Python, R and SQL to work with large-scale datasets in policy environments.