Building up a Data Science Team from Scratch

There are plenty of reasons for companies to incorporate data science and machine learning into their business. It can allow you to better understand and predict customer behavior, automate repetitive manual tasks, detect errors and anomalies faster, evaluate business decisions with data instead of mere intuition, get an edge over competitors, give marketing campaigns more punch, check a box for investors, attract more talent for the organization, or brag about it at conferences. Many companies face the challenge of building up a data science team from scratch and it can be hard to figure out how to start. In 2016, I was the first hire of a new data science team, with little infrastructure or strategy in place. Over the years, there were many different challenges for us to solve and mistakes to learn from as the team got more and more mature.