“Finding Your Fit” in Data Science this Monday, February 22!

Please join the MS in Data Science for our Finding Your Fit Panel coming up this Monday, February 22 from 6:00 – 7:00 PM PT! We have four phenomenal data scientists joining us, and while we have some questions prepared about what it was like for them to “find their fit” in the data science industry, we encourage students to bring your own questions for them, as well! You can RSVP here; the Zoom link will go out to students on Monday afternoon.



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Emily Ching is the Principal Data Manager on the Microsoft Mixed Reality Platform team. Her team focuses both on the Mixed Reality insights and building data pipelines that extract the right amount of insight nearly real time to bring efficiency to close the loop with customers. Emily is Mixed Reality women champ in driving diversity and inclusion.  In her free time, she is Destination Imagination WA coach in past 5 years.


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Jade Tabony is a data scientist at ExtraHop Networks, a Seattle-based software company specializing in enterprise cyber analytics for security, performance, and cloud. As part of the data science team at ExtraHop, she builds and maintains the Data Science research and analytics platform, as well as develops services to maintain the health of the data science software. Throughout her tenure both as a data scientist working at startups and as a mountaineer and rock climber, Jade is no stranger to being the only female on the team, which has led her to value diversity of perspective both in and out of the workplace.


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Hiwot Tesfaye currently works as a Sr. Data Scientist in SAS’ Health and Life Sciences Industry Solutions team where she advises SAS health care clients on how to best leverage SAS software to get the most out of their data driven initiatives. Before joining the health care team, Hiwot worked in SAS’s consulting division where she put her analytics expertise to use by developing visualizations and predictive models to address the division’s pressing business challenges. Hiwot is passionate about ensuring diverse perspectives are included in the AI and analytics space. She understands that diversity of thought and lived experiences is a powerful tool to bolster the practice of responsible AI and mitigate the risk of biased solutions being built and deployed. Hiwot is one of the founding members of SAS’s first Black employee resource group – the Black Initiative Group (BIG). She currently serves on the leadership council where she leads and participates in efforts to recruit, retain and promote Black talent at SAS.Prior to joining SAS, Hiwot was a graduate student at North Carolina State University’s Institute for Advanced Analytics. As part of her Master’s practicum, Hiwot lead a team of students in developing a model to predict patients’ risk of sub-optimal diabetes management for UNC Healthcare. Hiwot holds a MSc. in Analytics from North Carolina State University’s Institute for Advanced Analytics and a BSc. in Economics and Nutritional Sciences from University of Toronto.


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A self-described environmental nerd and data enthusiast, Jane Wu seeks to bridge the worlds of environmental engineering consulting and data science to make data-and community- informed decisions on how to improve our cities. She is involved in projects related to solid waste management, computer vision, mobility, renewable energy, green infrastructure, and wastewater treatment. In addition to her technical work as a consultant, she is on Arcadis North America’s Diversity & Inclusion Steering Committee where she is committed to making more diverse and inclusive work environments for Arcadis’ 5,500 North American employees. She has an M.S. from Columbia University in Earth & Environmental Engineering where she was an NSF S-STEM SEGUE Scholar, and a B.A. from the University of Pennsylvania in Environmental Science where she was a Benjamin Franklin Scholar. Jane’s pronouns are she/her/hers and identifies as queer, Chinese American, and from Mississippi.

By Eli Heller (He/Him)
Eli Heller (He/Him) Career Coach Eli Heller (He/Him)