People

Women in Data Science – Growing at UNCOMN

By

At UNCOMN, we challenge our team members to grow both personally and professionally. “Growing at UNCOMN” provides a snapshot of just some of the professional development our people take part in. In this installment, we hear from two of our Data Scientists and their experience at the Women in Data Science conference in St. Louis.

Women in Data Science

Rebecca Kalhorn –

In November, we attended the 2nd annual St. Louis Women in Data Science (WiDS) Conference at Washington University. WiDS started at Stanford in 2015 and has grown to include conferences globally with the goal to “inspire and educate data scientists worldwide, regardless of gender, and to support women in the field.” I certainly left the conference inspired and with increased awareness of some of the exciting work taking place in the St. Louis data science community.

UNCOMN attends Women in Data Science Conference St. Louis

The conference includes academics (WashU), large corporations (Microsoft, Bayer, Enterprise Holdings), hometown names (Schnucks, LaunchCode), and smaller businesses (Lexicon, Object Computing Inc.). The speakers’ topics for this year were, irresponsible conclusions from data–both unintentional and deceitful, using data in crop science for trait integration, and optimizing the grocery shopping experience and grocer profits through data. The conference attracts a wide range of attendees, allowing for diverse collaboration with WashU graduate students; scientists from Benson Hill Biosystems, Express Scripts, Daughtry, Bayer, Lexicon, and Capacity; a financial specialist from ConocoPhillips; the technical director for the Prepare.ai conference; and more. The conference truly has something for everyone interested in data science in St. Louis.

One particularly interesting talk was given by Dr. Kaitlin Daniels, an assistant professor of Operations and Manufacturing Management at Washington University. She studies the impact of the gig-economy on low-income families. Dr. Daniels specifically studies UberX and she found that the introduction of UberX to specific metropolitan areas increases the financial hardship of low-income families through a decrease in net pay. Childcare costs can sometimes be mitigated due to flexible hours but that is outweighed by a lack of medical benefits and added transportation costs.

Dr. Daniel’s talk was just one of the many types of talks at the conference. There was something for all levels of data scientists, the beginner to the advanced researcher. The vibe was welcoming and inquisitive, with presentations that were conversational as well as technical. If you are interested in data science, especially in the St. Louis community, I would encourage you to attend next year. I know I will!

 

Meliha Osmanovic–

As a recent college graduate who is only a few months into my career, I can say that attending the Women in Data Science conference was empowering and much needed for the transition I am experiencing. WiDS aims to inspire, educate and support women in the field – from those just starting their journey (such as myself) to those who are established leaders in industry, academia, government, and nonprofit government organizations. The conference offers a wide diversity within its women speakers, many of which I could personally relate to.

I had no idea how innovative one regional grocer is. They have a rewards app, curbside pickup, and an inventory robot. They identified that a rewards app and not just a rewards program provides better value to the customer while also gathering more customer data to identify purchasing trends.  They also have Tally, a shelf- auditing robot. It moves up and down aisles documenting inventory and provides quality control and constant monitoring, improving customer experience by leveraging the data Tally gathers.

Overall, I am extremely satisfied with the way the conference was conducted. It offered plenty of time for networking while providing food and beverages. I hope to attend again next year!

UNCOMN attends Women in Data Science (WiDS) Conference in St. Louis