10 questions data scientists should ask employers during a job interview

Data scientists are in high demand, taking the coveted no. 1 spot on Glassdoor’s Best Jobs in America list for the past three years, and boasting a median base salary of $110,000 for those with the right skillset. As nearly every company now has the ability to collect data, and the amount of data grows larger and larger, employees able to effectively organize and analyze this information for business insights are needed by many companies.

If you’re about to go on a job interview for a data scientist position, it’s important to prepare both for questions you may be asked, and for those you should ask your potential employer to demonstrate your interest in the role and company.

When hiring a data scientist, employers often look for business knowledge as well as mathematical and technical skills, said Jessica Hill, co-founder and data scientist at DataMinds.

“Questions from data science candidates around who in the organization will be using their work, what types of business problems the data science team helps to solve, and whether the organization is open to data scientists working with the teams implementing their insights to help drive successful outcomes are great questions to show that a candidate is interested in solving real problems rather than data science for the sake of data science,” Hill said.

Here are 10 questions that data scientists should consider asking on a future job interview.

“This shows me that the candidate is thinking about performance and what we consider important at the company,” said Sofus Macskássy, vice president of data science at HackerRank. “It also verifies alignment with cultural values.”

This demonstrates that the candidate wants to know exactly how the manager evaluates success or performance, and that they have a clear idea of what success looks like. “It’s a great litmus test for a good manager or leader,” Macskássy said.

This question will be specific to the company, and may be more appropriate for more senior data science candidates, Macskássy said.

“This shows me that the candidate values business impact and knows enough about the business to ask a business-related question,” Macskássy said. “Even if it is naive, because the candidate does not yet fully understand the business model or domain, it does show that the candidate is thinking in the right way about prioritizing work.”

When data science candidates ask questions about the overarching goals and priorities for the organization, it indicates that they intend to align their work with these goals and help drive the organization in the right direction, rather than working in a silo, Hill said.

“The best data science solutions emerge when a clear understanding of business needs is combined with deep understanding of the data,” said Pavel Dmitriev, vice president of data Science at Outreach. “A good data scientist would want to know what questions and needs business has, which they will need to work on answering.”

Candidates should ask questions about collaboration, said Ellen Houston, applied data science lead at Civis Analytics. “I appreciate when candidates ask about collaboration,” Houston said. “We work in cross-departmental teams, which requires both passion for learning and an interest in teaching others.