Tell us about your background.
Maya: I am from Israel, and was also able to spend two years in the US while in middle school. I loved science and studied physics, chemistry, and mathematics in high school. I have a B.Sc in Industrial Engineering, an MBA with honors from Tel-Aviv University, am a certified Project Management Professional, and a certified Data Scientist by the Technion, Israel's Institute of Technology. I’ve also spent time volunteering at SPACE-IL, a nonprofit organization which aims to land the first Israeli spacecraft on the moon and promote STEM education in Israel.
Pavel: I was born in a small town in the north of Kazakhstan (which was then a part of the Soviet Union), far away from the big cities. I was very interested in math and chess, and loved being a book worm in the town library after school. I won all of the math competitions I had access to. When I was 15 years old, my parents and I moved to Israel. After high school, I got my B.A. in Economics and Business Management and then completed a master’s degree in Financial Mathematics.
How did you get interested in data science?
Maya: I’ve always been interested in the sciences. Throughout my career, I’ve discovered time and again how powerful and insightful data can be. I decided to pursue the data scientist certification to delve deeper and knew shortly after graduating that AI was the career path I wanted to pursue.
Pavel: I worked in the field of financial debt markets modeling for about seven years. In the last two years I was engaged in several projects where finance meets data science. Since then I knew that data science is what I wanted to pursue so decided to leave the financial field.
What are you currently working on?
Maya: I'm a data scientist and a data product manager, currently working on an AI project that transforms satellite analytics into actionable intelligence so that ground failures can be identified early.
Pavel: I’m at data scientist and innovation coach at the NEC Innovation Lab in Tel Aviv where my research focuses on tabular and computer vision problems.
How did you first discover WiDS?
Maya: I heard about the WiDS 2021 Conference and Datathon through a LinkedIn post. I was inspired by the mission of WiDS to educate and inspire data scientists around the world and to support women in this field, and was also inspired by the Datathon challenge focused on diabetes and patient health.
Pavel: The WIDS Datathon 2021 was my first experience with WIDS. Now I have learned about all of the WiDS webinars and events and I am excited to make an impact on such an important initiative.
Tell us about your Datathon experience.
Maya: The story of our Datathon team is an interesting demonstration of the WiDS initiative's success. As a Data Scientist, I wanted to participate in the datathon in order to learn, enhance my skills and develop professionally. The public leaderboard showed a team of two men who were in the lead. Each team is required to be at least half women, so in spite of not knowing them previously, I reached out and this was very helpful in getting me to join their team. It was great learning data science from my veteran teammates during the competition.
What started as a Kaggle collaboration, blossomed into a professional partnership so strong that we decided to extend our partnership to Phase 2: The Excellence in Research Award competition. This enabled us to share more details about our work, and contribute to the broader development of collaborative data science in the health data community. Both phases were very hard work, and we are very proud and honored to win 3rd place in the datathon and first place for the research award. We hope to make an impact, and are grateful for the WiDS initiative and for Kaggle for granting us this opportunity.
How has WiDS made an impact on your life and/or work?
Maya: I have gained a great deal from WiDS, both in my personal and professional development. I was able to take part in data science challenges, share knowledge with remarkable colleagues, and have a positive impact beyond anything I could have imagined. I feel very fortunate, proud and honored. The experiences have been empowering and inspiring. It gives me a sense of possibility in pursuing the next big data science challenges, making an impact, and giving back.
Pavel: As a child I was a dreamer and kept following my dreams all my life, but even in my bravest dreams I didn’t imagine that my work would be honored by top researchers from the top universities.
What comes next for you? And what are your hopes for women in the data science in the future?
Pavel: I am enthusiastic about the work WiDS is doing to teach and share knowledge about data science
around the world. I hope the community continues to grow and inspire many others to contribute and do great things.
Maya: I plan to continue participating in data science challenges, solving real-world problems for the greater good, and making an impact. I hope that WiDS will continue to thrive, building a powerful community, encouraging women to pursue careers in data science and doing so in a way that provides amazing opportunities for women to grow professionally. My wish is that this generation of women in data science believe in themselves and accept a broader perspective of the world. I hope they will be encouraged to take risks, explore new challenges, build strong communities, and live the lives they have always dreamed of.