What are the 6 Essential Qualities of a Great Data Scientist?

You’re looking for a data scientist and the resumes are pouring in. Most of the job candidates have the hard skills it takes to succeed: strong technical skills, a solid mathematical background, some programming knowledge, etc. — but it’s the soft skills that will set the successful data scientist apart from the unsuccessful one. What qualities are essential for filling your position?

1. A Love for Solving Problems

Unprocessed data is a bit like a gigantic jigsaw puzzle. For someone who doesn’t like solving puzzles, it looks like a big, confusing mess. A good data scientist looks at the jumble of raw data and sees a thrilling challenge. Find a candidate that can’t wait to get their hands on the messiness of your raw data and put it all together to make sense out of it.

2. An Inquisitive Mind

A good data scientist is curious to see what secrets the data holds. (S)he isn’t trying to make the data back up a particular point of view, but instead is dying to know what truths the data can lead to. Natural curiosity is essential for a good data scientist, because innate curiosity drives them when things get difficult. Things always manage to get difficult.

3. A Streak of Creativity

Too often, we separate people into two categories — left brain folks and right brain folks. We don’t always associate hard sciences like big data with the creative arts, but a good data scientist will have a streak of creativity that allows them to think of new ways to approach the data, new ways to analyze the data, new questions to ask the data, and new ways to present the analytical findings.

4. Strong Communications Skills

A data scientist often serves as a liaison between the tech folks and analytics team(s) and the business side. (S)he needs to be able to hear what the business people are saying and translate that into tech speak, as well as to understand what the tech side says and translate that back into business jargon. Look for a candidate who can easily communicate with both sides of the big data divide.

5. Knowing When to Press On and When to Stop

If you find that candidate who loves solving puzzles and has a natural curiosity, those strengths will drive them to push beyond obstacles and find solutions when things are difficult. But it’s also a pitfall to become dogmatic and push on when it’s time to step back, let go, and perhaps scrap or completely rethink a project.

6. An Understanding of Database Design and Management

Whether you’re dealing with structured data, unstructured, or a combination, the data scientist needs to know how databases work, how to build and maintain a database, and how to develop a database infrastructure that can manage semi-structured and unstructured data sets. Not many applicants will have Database Administrator on their resumes, but if you can find one with at least a basic knowledge of database design and administration, this skill is a huge plus.

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