Get to know the women behind the data science. Leading women in data science share their work, advice, and lessons learned. Hear about how data science is being applied and having impact across a wide range of domains. Join hosts Margot Gerritsen and Chisoo Lyons in the open and informal conversations with our many inspiring guests.
Episode 33
Allison Koenecke, currently a postdoc at Microsoft Research and soon to be assistant professor at Cornell, discusses her decision to pursue a career in academia focused on algorithmic fairness and causal inference in public health.
Episode 32
Karina Edmonds, Global Head of Academies and University Alliances at SAP, has spent her career building bridges between business and academia. She is passionate about promoting fairness in data science by bringing more young people, women, and underrepresented groups into the field.
Episode 13
Marzyeh Ghassemi, an assistant professor at the University of Toronto, is focused on Healthy ML—applying machine learning to understand and improve health.
TOPICS: Data Science as a Career
Jane Lauder, Chief Data Officer at Estée Lauder, explains how Estée Lauder combines data science with creativity to connect with their consumers, create aspirational products and support the longevity of their brands.
TOPICS: Algorithms, Data Generation/Collection
Priya Donti, Executive Director of Climate Change AI, explains multiple ways that machine learning and AI can be used to mitigate climate change. Her work at the intersection of climate change, computer science, and data science led her to co-found Climate Change AI, our partner for the WiDS Datathon 2023 challenge to improve long-term weather forecasting.
TOPICS: Data Science as a Career
Lesly Zerna, Google Developer Expert at Universidad Privada Boliviana, is a Bolivian researcher, teacher, mentor, content creator, and software developer. Shares her passion for learning and teaching data science and artificial intelligence. Lesly says learning works best when you know your personal learning style and apply that to practical topics you are interested in.
TOPICS: Algorithms, Data Generation/Collection, Values
Leda Braga is founder and CEO of Systematica Investments, a hedge fund known for using data science-driven models to support its investment strategies. She explains how systematic investment management is data science applied to investment and how she believes it is the future of the financial industry.
TOPICS: Data Generation/Collection, Data Science as a Career
Jessica Bohórquez, a researcher at the University of Adelaide in Australia and an industry consultant, is using AI and pressure transients to inspect and monitor water pipelines to detect leaks. She discusses her PhD research, working in industry and her advice for pursuing a career in data science.
TOPICS: Data Generation/Collection, Data Wrangling
Dr. Karolina Urbanska, a data scientist working for Teach First in the UK, has spent her career using data science to better understand human behavior. She discusses her work as a data science and psychology researcher, her decision to leave academia, and her learnings along the way.
TOPICS: Data Science as a Career
WiDS Co-Founder Margot Gerritsen welcomes her new podcast co-host Cindy Orozco, as they interview each other about their career paths to data science, coping with the imposter syndrome, and successfully juggling busy lives.
TOPICS: Values
Tahu Kukutai, a professor at the University of Waikato in New Zealand and a Māori woman, is leading data sovereignty initiatives that advocate for indigenous data ownership, guardianship, and governance.
TOPICS: Data Science as a Career, Featured, Values
Allison Koenecke, currently a postdoc at Microsoft Research and soon to be assistant professor at Cornell, discusses her decision to pursue a career in academia focused on algorithmic fairness and causal inference in public health.
Margot Gerritsen was born and raised in the Netherlands, and after getting her PhD at Stanford, she.spent time in New Zealand in the Department of Engineering Science at the University of Auckland, returning to Stanford in 2001 as faculty member in Energy Resources Engineering. Margot specializes in the development of computational methods for renewable and fossil energy production. She is also active in coastal ocean dynamics and yacht design, as well as several other areas in computational mathematics including search algorithm design and matrix computations. Margot also Chairs the Board of Trustees for SIAM (Society for Industrial and Applied Mathematics).
Chisoo was born in South Korea and grew up living in Indonesia, Germany, and Jordan, before moving to the US. She attended University of California Berkeley and received a bachelor’s degree in Industrial Engineering & Operations Research and continued with her master’s focusing on Operations Research. Living in different parts of the world cultivated her ever-present curiosity about people and cultures. Chisoo worked for FICO, a global analytic and decision management company, applying data science to developing, consulting, and implementing decision support solutions for her clients. Her corporate career culminated in leadership roles managing innovation and lines of business. Now, as the Chief Program Director of Women in Data Science, Chisoo is thrilled to be in service of a global community of amazing women doing extraordinary work in the field of data science.
