Tristan Bergh is a systems thinker and data scientist living in Cape Town, South Africa. He studied aeronautical engineering before working as an enterprise software engineer. He worked as an architect on AFIS implementations in Southern Africa, moving into middleware for large fin-tech systems. He restarted his system modeling and machine learning consulting services through 2014, delivering predictive analytics models in healthcare and other domains.
Ankit Gupta is a data scientist at Crisis Text Line, a New York-based not-for-profit tech startup providing 24/7 free text-based crisis support to individuals. At Crisis Text Line, Ankit developed an AI-driven triage system that detects signals of suicidality within the first few messages sent by texters. Using the triage system, the counselors can serve 93% of at-risk texters in under five minutes.
Genevieve Patterson is the chief scientist at TRASH, a startup that is developing computational filmmaking tools for mobile iphono-graphers. Before that, she was a Postdoctoral Researcher at Microsoft Research New England. Her work is about creating dialog between AI and people. Her interests include video understanding, visual attribute discovery, human-in-the-loop systems, fine-grained object recognition, medical image understanding, and active learning. Genevieve received her Ph.D. from Brown University in 2016 under the direction of James Hays.
Peadar Coyle is a Data Scientist and Engineer based in London. He regularly speaks at conferences and has written a book consisting of numerous interviews with Data Scientists throughout the world. He is also a passionate Open-Source evangelist, himself a supporter who has contributed to PyMC3. Most recently, he founded a stealth startup that is working on hyper-personalized audio.
Nick Gaylord has worked as a data scientist in the Bay Area for about the last 5 years. Currently, he’s a member of the Johnson & Johnson Health Technology team, and prior to that, he has worked in different fields ranging from small business revenue analytics to enterprise machine-learning-as-a-service platforms. Like many data scientists, he started out as an academic before transitioning to industry, in his case earning a Ph.D. in Psycholinguistics from the University of Texas at Austin in 2013.
Conor Dewey is a data scientist at Squarespace who spends his time thinking about growth and engagement. He frequently shares insights from his experience interviewing at top companies. More generally, he offers resources and advice on Medium and Github in the hopes of ‘open sourcing’ his journey to data science. Conor also manages a weekly data science newsletter with 1000+ subscribers.
Martina is a physicist and works as Data Science Lead at Mallzee, based in Edinburgh (Scotland). She loves looking at data regardless of the topic and area and believes the most enjoyable thing in Data Science is analyzing your data, finding the one you need for your question, and producing facts out of it. Throughout her education and job experience, she worked with data in epidemic dynamics, linguistics, and fashion. She also loves producing hand-crafted data visualizations and keeps studying and improving, whether it’s about Machine Learning or leadership topics.
Jim Leach is a data scientist, originally from the North of England, but now based in Atlanta, Georgia. After studying chemistry at university, Jim joined the consulting firm KPMG and began his career as a data analyst. He later returned to university, taking a sabbatical to study for a Master in Business Analytics at Imperial College, London. In his work, he is a passionate R user and developer and enjoys thinking about data visualization and how to communicate effectively using data. In his free time, he enjoys board games, music, cooking, and being outdoors.
Francisco Carrera Arias, B.S. is currently a data scientist/analyst for MotionPoint Corporation and a research assistant for the Clinical Systems Biology group at Nova Southeastern University. His current work entails performing a variety of data analyses to better inform business decisions as well as using discrete logic to analyze complex biological regulatory networks for the purposes of identifying and simulating treatment courses for chronic illnesses such as Gulf War Illness.
Matthias, a linguist turned data scientist, finished his Ph.D. in May 2018 and is currently working as a Manager, Data Analytics at LiveIntent. In his day-to-day, he builds dashboards and models, and runs analyses that drive business decisions and provide stakeholders with meaningful access to data. He enjoys empowering people with data by visualizing and analyzing various types of data visually and/or with statistical and machine learning approaches. He is an avid R/RStudio/RStudio Connect user.