Rev 2018 was the launch of Domino’s Data Science Leaders Summit, and we were excited to bring fresh ideas to the event through our Domino Diversity & Inclusion Club travel grants. Our goal was to make a contribution to the ongoing effort to break down barriers that have kept the profession of data science from being diverse and inclusive, by extending travel and accommodation to diverse applicants.
We asked our Domino Diversity & Inclusion Grant recipients for some takeaways on Rev, as well as what brought them to the conference. You can read about them below (some excerpts edited for length and clarity):
Marielen is a Data Scientist at TOTVS, a Brazilian multinational software company, who previously worked with CERN on neural network applications, development of 3D sound, and processing of communication signals through Bluetooth Low Energy for the perception of human presence. She co-founded Sao Paulo’s chapter of Women in Machine Learning & Data Science.
The panel on Data Responsibility (Positive Social Impact Through Ethical Data Science) made me think about my work and how I really want my colleagues to start discussing topics like this. It was an honor to be with Wes McKinney (creator of Pandas) and got me thinking more about open source projects. I can’t wait to go next year!
Ramon is finishing his Masters of Data Science at University of the Pacific in Sacramento, California. He recently worked with the USDA as a statistician, and is interested in the underlying concepts of data science (creating algorithms, utilizing large databases of information, and applying economic concepts within companies). He has a wide breadth of life experience, and previously worked at the Mexican Consular, as well as the U.S Embassy in Madrid, Spain.
As a grad student of data science, attending the Rev conference was invaluable experience. I was able to learn about the data science community’s current issues. For example, an ongoing theme was that we need to standardize some of the processes in the data science field to bring more productivity to companies. Overall, the conference was great. I will definitely attend in the future as a data scientist.
Theresa is currently pursuing her PhD in Statistics and Machine Learning at Carnegie Mellon University. Her research focuses on understanding the characteristics of precancerous cells from photographs, with the long-term goal of developing drugs that prevent cancer altogether. She is particularly passionate about empowering non-statistical researchers to understand and explore their data. In her free time, she provides free statistical consulting to non-profit organizations.
Rev was the rare kind of conference that delivered on what it promised. As an academic, I was hoping to learn industry challenges, viable solutions from industry leaders, and to discuss data science culture with current and aspiring leaders. Speakers were accessible, and topics ranged from ethical concerns in data science to Monte Carlo methods for feature selection. I was impressed by the caliber of attendees I was able to socialize with. My highlight was discussing data science training with Cassie Kozyrkov, Chief Data Scientist at Google.