Demand for data scientists continues to grow, and the job market is hot for those with the right skillset.

Data science job candidates can expect a variety of technical questions and exercises that depend upon the position and the company. But outside of tech know-how, adequately describing your skills with communication, teamwork, and creative thinking is key.

“To assess if a candidate can be successful as a data scientist, I’m looking for a few things: baseline knowledge of the fundamentals, a capacity to think creatively and scientifically about real-world problems, exceptional communication about highly technical topics, and constant curiosity,” said Kevin Safford, senior director of engineering at Umbel.

SEE: Job description: Data scientist (Tech Pro Research)

Demonstrating that you have a strong understanding of the business at hand and how data can be used to reach business goals will also set you apart.

“In addition to many technical questions–knowing your algorithms, knowing your math–a great data scientist must know the business and be able to bring strong ideas to the table,” said Rick Saporta, head of data science at Vydia. “When hiring, I would rather have one creative data scientist who has a strong understanding of our business, than a whole team of machine learning experts who will be in a constant ‘R&D’ mode.”

Here are 10 questions that you might be asked during an interview for a data science job, from a number of people currently working in the field.

  1. Describe a personal or professional project in detail.
  2. Tell me about a time you had to work with someone who is not data-savvy on a data science project.
  3. Tell me about a time you had to work with very messy data.
  4. Tell me about the most complicated data project you have worked on, and what you were able to do in order to achieve success.
  5. What are your favorite data science tools and techniques?
  6. How do you generate results when you don’t have enough data or your data is corrupt?
  7. Tell me where you think data science is heading–both in the short term, and in the long term.
  8. Can you outline your process for diving into data and sharing findings with the broader team?
  9. What is the size of the biggest dataset you have built models on?
  10. Tell me about the most unique insight derived from a data set that you compiled.

SEE: Sensor’d enterprise: IoT, ML, and big data (ZDNet special report) | Download the report as a PDF (TechRepublic)

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