What We Learned Analyzing Hundreds of Data Science Interviews - Springboard Blog

Top data science teams around the world are doing incredible work on some of the most interesting datasets in the world. Google has more data on human interests than every 20th century researcher, while Uber seamlessly coordinates the itinerary and pricing of more than 1 million trips every day. With machine learning, and artificial intelligence, top data science teams are changing the way we ingest and process data, and they are coming up with actionable insights that impact the lives of millions. What if there were common patterns between the interviews top data science teams were giving that would let you master the data science interview process? What if the specific differences between various teams and their interview practices could be enumerated so that interviewing with a top data science team were more akin to a science than an art?