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Activity Number: 50 - Industry Applications for Environmental Statistics
Type: Topic Contributed
Date/Time: Sunday, August 7, 2022 : 4:00 PM to 5:50 PM
Sponsor: Section on Statistics and the Environment
Abstract #322443
Title: Environmental Statistics in Computational Agriculture
Author(s): David Clifford*
Companies: X, the moonshot factory
Keywords: computational agriculture; career development; leadership; tech
Abstract:

In 2015, I moved away from roles in agricultural research to take up an industry role which offered the opportunity to work in a fast-paced start-up environment, to get closer to users of my research, and to extend my interest in leading research teams. This was simultaneously the scariest and most rewarding decision of my professional career. Since then I have had three roles leading data science teams in different industries and different-sized organizations, and have had a wide variety of experiences which I would not have otherwise encountered. I will share some of my learnings from these opportunities, both personally from my perspective as a data science team lead, as well as from team members at different stages of their careers. While many skills learned in academia and technical training will transfer seamlessly, how those skills are used, and the soft skills that accompany them, will be challenged in different ways depending on the culture on how research, data-science, engineering and product of the company intersect with each other.


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