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Women in Data Science: A Panel Discussion
26 February 2025, 5:00 pm–6:00 pm
Join us for this Social Data Institute event where we explore the topic of women and data science.
This event is free.
Event Information
Open to
- UCL students
Availability
- Yes
Cost
- Free
Organiser
-
UCL Social Data Institute
Location
-
Room G22North - West WingGower StreetLondonWC1E 6BTUnited Kingdom
About the event:
Join us for an inspiring Women in Data Science panel event, where we showcase women from diverse areas within data science—spanning academia, industry, and beyond. This event aims to highlight opportunities for women in the field while fostering an open discussion on the challenges and experiences of being a woman in data science.
This is a fantastic opportunity for students to engage with accomplished professionals, ask questions about their careers, and gain valuable insights into navigating the field. Whether you’re just starting your journey in data science or looking for guidance on your next steps, this event is designed to support and inspire you.
Speakers:
Fem Alonge is a Senior Data Scientist at National Grid
Hannah Berry is an Analyst Developer at Sumitomo Mitsui Banking Corporation (SMBC)
Professor Jennifer Hudson is Vice-Provost (Faculties), University College London, and Professor of Political Behaviour.
Julia de Romémont is a Lecturer in Quantitative Research Methods and Political Science in the Department of Political Science at UCL.
Stay after the panel for a drinks reception, where you can network and continue the conversation in a relaxed setting.
Don't miss out—reserve your spot today!
This event is for all UCL Social and Historical Sciences undergraduate students, especially those on data science pathways.
About the Speakers
Fem Alonge
Senior Data Scientist at National Grid
Fem works in the UK Energy Market Analytics team, modelling long-term energy scenarios to support the transition to net zero. She holds a BSc in Social Sciences with Quantitative Methods from UCL, where she focused on developing strong data skills.
She began her career as a Data Analyst at the Department for Business, Energy & Industrial Strategy (now the Department for Energy Security & Net Zero), analysing data to inform Smart Meter rollout policy. She later joined the central data science team, where she worked on natural language processing for green jobs analysis. During her time in the civil service, she also completed a Master’s in Geographic Data Science from Birkbeck, University of London.
Passionate about using data science to tackle challenges in the energy sector, Fem is particularly interested in how machine learning can be used to flex and reduce energy demand.
Hannah Berry
Analyst Developer at Sumitomo Mitsui Banking Corporation (SMBC)
Before making a switch into FinTech, by way of a coding bootcamp, she was Head of Reference Data at Dods Group, a political consultancy. With an academic background in political science and philosophy Hannah has utilised data science principles throughout her varied career, demonstrating the versatility and transferable nature of the discipline.
Professor Jennifer Hudson
Vice-Provost (Faculties) and Professor of Political Behaviour at University College London
Professor Hudson is the Director of the Development Engagement Lab (DEL), a multi-country research programme working in partnership with 30 development INGOs and government ministries to understand public support for aid and sustainable development.
Professor Hudson’s research has been funded by the Bill & Melinda Gates Foundation, Economic and Social Research Council (ESRC), Danish Council for Independent Research, Nuffield Foundation and Leverhulme Trust.
Julia de Romémont
Lecturer in Quantitative Research Methods and Political Science at Department of Political Science at UCL
Julia de Romémont is a Lecturer in Quantitative Research Methods and Political Science in the Department of Political Science at UCL. Her research interests lie in the fields of political economy, public opinion and behaviour and the politics of migration. In particular, in her research, she aims to better understand how and when anti-redistributive, exclusionary and reactionary attitudes and political behaviour emerge, using diverse quantitative methods techniques, including causal inference approaches and survey experiments.