Hiring a new member to your team is always a daunting task. Now combine that with looking to fill “The Sexiest Job of the Century”, Data Scientist, and you have quite the conundrum on your hands.
To start, let’s discuss the four major categories of Data Scientists:
Algorithms Expert These are the people who will ask you what questions you want answered. They then try to answer these questions by matching the form and format of your available data to a set of Machine Learning or Optimization techniques. Algorithms Experts usually come from a Computer Science, Electrical Engineering, or Mathematics background.
Data Miner Data Miners are “why” scientists who ask why you’re asking the questions you are asking. They then try to find patterns in the data and build individual or derived Performance Metrics that will help focus the business in their direction and outcomes. Data Miners usually come from a science-based background like Physics, Biology, or Chemistry.
Data Wrangler Just like a cowboy, a data wrangler will manage your data flows and makes sure data is internally consistent. They look at your raw data and say, what do you need from this and what are you missing, then architect and build the systems to accomplish this. Data Wranglers come from a diverse set of backgrounds.
Statistician This is a mathematician who looks for patterns in your raw data. They are the classic actuary, where given a set of possible outcomes, they try and look for patterns in your data stream that will try to predict any of the outcomes. Statisticians usually come from Applied Math or Statistics background.
It’s interesting to note that most Data Scientists are a blend of more than one category, and that’s a good thing as Data Scientists are required to fill multiple roles.
In the next installment, we’ll talk about hiring your first Data Scientist and how they fit into your team.
Andrew Eichenbaum specializes in data mining, data modeling, and artificial intelligence.