• ABOUT THE Authors

    Carl Shan

    Carl is a Data Science for Social Good Fellow in Chicago, where he works with President Obama’s former Chief Scientist on applying machine learning and data science to pressing policy issues. He’s written extensively on his experiences in applying machine learning to social issues. An avid reader, he co-authored The Data Science Handbook to help bring stories and wisdom from pioneering data scientists into the lives of as many readers as possible. When not mired in data, Carl can be found at a pool table, or pretending to know the lyrics of the latest hit pop song.


    Carl holds an honors degree in Statistics from UC Berkeley.

    Henry Wang

    Henry is currently based in London working on a turnaround of a UK based specialty finance business. Prior to this, Henry worked on growth equity investments in renewable energy companies based in the US. He enjoys competing in data science competitions his spare time and is currently very interested in generalization guarantees for stochastic gradient based optimization in machine learning. Henry holds a degree in Statistics from UC Berkeley, you can learn more about him at www.henrywang7.com

    William Chen

    William is a data scientist at Quora, where he helps grow and share the world’s knowledge. He is also an avid writer on Quora, where he answers questions on data science, statistics, machine learning, probability, and more. William co-authored this book to share the stories of data scientists and help others who want to enter the profession. For fun, he enjoys speed-solving Rubik’s cubes, building K’NEX ball machines, and breaking out from “escape rooms”. Check out his recent projects (like The Only Probability Cheatsheet You’ll Ever Need) on his website.


    William holds a Bachelors in Statistics and a Masters in Applied Mathematics from Harvard.

    Max Song

    Max is a data scientist currently working on secret projects in Paris. Previously, he was the youngest data scientist at DARPA-backed startup Ayasdi, where he used topological data analysis and machine learning to build predictive models. He wrote a popular post about his journey to become a data scientist on Medium, and enjoys the craft of writing. He co-authored the Data Science Handbook to share the the wisdom of pioneers for those looking to trailblaze their own data science paths. When not feverishly coding, he can be found playing improv games and seeding an intellectual gathering (Salon) in far-flung corners of the world.

    At the time of writing, he is on leave from Applied Mathematics-Biology at Brown.