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There’s a running joke in data scientist circles that companies are looking for some magical, mythical unicorn of a data scientist who can snap her fingers and instantly materialize a stack of useful graphs and algorithms. There are at least two problems with these overblown expectations. First, no one person can do everything. And second, many companies don’t really understand what data scientists do or what they want to hire them to do.
Last week, an email from a data scientist named Will started circulating the Internet. He applied, interviewed, and was rejected for an analytics position with the online dating startup HowAboutWe.com. In what was not the most mature response to a job rejection, he replied to the company via email and CC’ed a slew of news outlets.
Still, he raised a good point in asking how a company can hire a data scientist when they aren’t completely sure what they’re even looking for. Will wrote: “Why wasn’t I asked a few simple questions about SQL which almost every other serious player in the industry asks during their first phone screens?”
This week’s five articles are about Will’s experience and how companies can revisit the question “What does a data scientist do?”
- No Fury Like a Data Scientist Scorned at insideBIGDATA: “You guys are taking on some big names in the game. You NEED people that bring toughness and variety to the picture. And if you’re making snap judgment calls for your hiring process, then that can only suggest your company doesn’t take the data and analytics seriously.”
- Traits That Make A Great Data Scientist at InformationWeek: “A computer science background is essential for data processing and manipulation. Advanced math skills, including a solid background in calculus, geometry, linear algebra, and statistics, are required for understanding the basis for algorithms and other data science tools, the report said. And domain expertise helps the data scientist understand the problem at hand and how to measure it.”
- Good Data Scientist Hunting – The Sexiest Job of the 21st Century at HeraldBoy: “Part of the reason it’s so hard to pin down a meaningful definition of a data scientist, is because the scope of what a data scientist does seems impossibly broad. The organizations that make some headway on developing their data science capabilities are the ones that emphasize the cultivation of data science teams – which come together with a variety of backgrounds and technical capabilities – instead of trying to identify and recruit the proverbial “unicorn,” single rock star all-round data scientist.”
- How to Pick a Data Scientist, the Right Way at ITProPortal: “As a business, you have to choose which aspect you want to prioritise, and what’s important for the data you’re dealing with. You have to take a low-hanging fruit mentality for data. That means you find data that’s possible to extract, and that has value to someone in your organisation.”
- It Takes Teams to Solve the Data Scientist Shortage at The Wall Street Journal: “For example, Monster Worldwide has built up a team of data crunchers, statisticians, business analysts, computer scientists and ‘navigators’ who can explain findings to managers. And American International Group, Inc. is assembling a ‘Science’ team of statisticians, business analysts, project managers, systems architects and engineers for its Property and Casualty business.”
Download our guide to learn more about what data scientists do and how can help your business:
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