Lauren S. Moores, a.k.a. “the Data Queen,” is Head of Data Sciences Innovation for FL65 and Invaio Sciences, two companies launched by Flagship Pioneering, a venture capital and private equity firm dedicated to creating breakthroughs in human health and sustainability and build life sciences companies. She is also Chair of the Data Advisory Board for USA for UNHCR, a non-profit organization supporting the UN Refugee Agency, and a Teaching Fellow at the Harvard Business Analytics Program. We spoke to Lauren about building data science systems for companies of all sizes, ensuring those platforms maintain high data quality, and accounting for bias in data analytics. (Read Part 1 of our interview here and Part 2 of our interview here.)
Continue reading “Accounting for Bias in Data Analytics: An Interview with Lauren S. Moores, Part 3”
Gordon Wong has been working with data since the early 90’s. His accomplishments include building Fitbit’s data analytics platform from the ground up and serving as HubSpot’s VP of Business Intelligence. He has also worked or consulted for leading brands such as ezCater, edX, and ZipCar. In all his engagements, Gordon focuses on repeatable processes, continuous insights, and team building. In Part 2 of our interview, we spoke to Gordon about data coverage and other pillars of data science, and the importance of testing for data quality. You can read Part 1 of our interview 
Data engineering teams need to be able to find and fix data quality problems quickly. In part 2 of our interview with Michal Klos, Michal discusses the challenges of discovering and troubleshooting data quality problems in pipelines. Michal is Sr. Director of Engineering at Indigo Ag, where he is helping the fight against climate change. Michal has been leading data engineering and platform teams for nearly two decades. Before joining Indigo Ag, he built and scaled massive data platforms at multiple companies, including Localytics, Compete, and WB Games. You’ll find Part 1 of our interview with Michal