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.
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.
Thomas is a bioinformatician, turned software engineer, who enjoys developing tools for data scientists. His main interests are in the tools that bring the scientist closer to their data, whether it be through intuitive and powerful APIs or through visualization. He describes himself as a creative spirit who enjoys photography as well as generative art and graphic design, and he tends to try and combine this with his interest in programming whenever possible. Thomas lives just north of Copenhagen with his wife and two kids.
Christopher Peters is a full-stack data scientist at Zapier. He was both Zapier and Treehouse's first data scientist. Prior to his work as a data scientist, he was a research associate at LSU’s Center for Energy Studies where he was an energy economist. He has a real passion for working with, sharing, visualizing and analyzing data of all kinds using statistical, visual and machine learning techniques.