Hiring data scientists? You’re doing it wrong

Photo credit: Mykhailo Ridkous / 123RF

Dear world,

We are looking for someone to fill an upcoming gap in our business model. We are not exactly sure what you will be doing, but we are sure our shareholders will love the idea that we have data scientists.

You will report to someone who does not understand what you do, and you will often be met with skepticism when you present your solutions to the management.

Candidates must possess the following:

• B.Sc in Computer Science
• M.Sc/PhD in a quantitative field
• Three to five years of experience in a research-focused position handling back-end frameworks, application development, and web hosting
• A deep knowledge of both neural networks and statistical methods
• Five years of programming experience
• Two to three years of experience in database management
• Five years of experience in our domain (e.g. healthcare, marketing, etc.)
• Advanced knowledge of SQL, Python, R, Matlab, Java, C, C++
• Two to three years of experience publishing research papers in AI, NLP, or computer vision (all three preferred)
• Experience with Spark, Hadoop, and Pig…and Horse

A person that hardly exists

How many people in the world do you think fit this bill? And what number of those people have the soft skills to be customer facing, client facing, management facing, yet analytical, creative, and intelligent? We are asking the wrong things from data scientists and we are looking in the wrong places.

There is no possible way that a data scientist will use all these tools in one company. It’s even less likely that someone knows all these languages. Data science is more about the intelligent use of programming rather than programming itself.

You are not hiring programmers

Stop focusing on degrees and credentials, but on proven real-world experience. The person does not even have to be a formal data scientist. Here is my main goal when I look to bring on a new member to our ML team:

What we want:

• People who are intelligent, explorative, and passionate—instead of experienced
• People with an ability to take cloudy, uncertain ideas and build them into finished products

What we offer:

• An interesting team and strategy and the opportunity to work on cutting-edge technology
• Room to grow and an understanding of what they want to learn and help them get there
• An understanding that everyone in the team is equal

Start with what matters

The most difficult skills to find when it comes to data science are not tied to a degree or specific work experience. It is the explorative nature, the push for optimization, the results mindset, the never-give-up attitude, and the willingness to learn that makes a good data scientist. When I look to hire people in my team, these are the most important skills. Everything else is gravy.

Create a job that you would want to take

Managers should write their own job descriptions

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