Cancer Data Science Pulse

Job Interview Questions for Cancer Data Scientists and How to Answer Them

If you’re looking to explore a career in data science with NCI, or elsewhere, we want to make sure you’re prepared. Job interviews can be intimidating, and preparation is key to advancing your interview skills. We read through and selected six questions from LinkedIn's interview questions for hiring data scientists. Then, we asked CBIIT’s own Dr. Daoud Meerzaman, Computational Genomics and Bioinformatics Branch chief and hiring manager, for his thoughts.


Discover the skills often analyzed by hiring managers, hear examples of what one NCI hiring manager is looking for in a data scientist, and see additional questions that Dr. Meerzaman personally asks during interviews.

Hard Skills

Hard skills are the technical abilities required for the job. These skills represent a candidate’s ability to perform a task.

“Which data analysis tools and programming languages are you most proficient in?”

Daoud Meerzaman: For this question, it’s very important to know which tool the candidate has used and how he or she has used it to analyze big data. NCI cancer data scientists focus on artificial intelligence, machine learning, and deep learning tools for research. If you’ve worked with these tools, I would want to know a project you applied these methods to, and if it included big data analysis.

“Describe an original algorithm you’ve developed, including how you made it and for what purpose.”

Daoud Meerzaman: Often when hiring managers interview candidates, the candidates describe what they know. This question, for me, serves as a way to discover what the candidates can do in this line of work. Just because they have learned how to develop an algorithm does not mean they know how to apply it. Learning something is very different from applying it. I want to know if you applied your algorithms to answer any scientific questions.

Daoud Meerzaman

Behavioral Intelligence

Behavioral intelligence is a person’s ability to interact effectively with others in the workplace. These questions will help a hiring manager understand how the candidate has approached and reacted to past situations.

“Tell me about a data science project you’ve worked on where you encountered a challenging problem. How did you approach and overcome the challenge?”

Daoud Meerzaman: I will always ask this during interviews. It’s important to find out how the candidate behaves in terms of interpersonal conflict. More generally–how does the individual deal with situations where there is interpersonal conflict? A hiring manager is looking to see how the candidate handled the problem, which can assist in understanding the personality of the individual.

“Tell me about a time when you had to clean and organize a big data set.”

Daoud Meerzaman: This is a very generic, unstructured data question. For it to apply to the cancer data science field here at NCI, I would add, “How do you approach cleaning and organizing medical records, sequencing data, or proteomics data sets?” Hiring managers at NCI want to know the type of data the candidates have cleaned and how they go about treating outliers in a data set.


Soft Skills

Soft skills help assess a candidate’s cognitive abilities. It’s a combination of people skills, social skills, communication skills, emotional intelligence, and personality traits.

“Have you contributed to any open-source projects?”

Daoud Meerzaman: Data sharing is big for NCI. Being able to analyze data from different projects is one way to advance our understanding of cancer. If a candidate contributes to open-source projects, I will want to know which ones. People who take advantage of crowdsourcing means they also use and contribute to other people’s expertise. Take collaborative work, for example. What kind of crowdsourcing projects have you worked with? Private, academics, government? This information helps give hiring managers a better sense of this person’s capabilities.

“What makes you well-suited to work in data science?”

Daoud Meerzaman: I need to know if the candidate possesses qualities such as organization skills, an interest in working with data, attention to detail, and the ability to see both the big picture and small details. For instance, as data scientists, it is crucial to comprehend the molecular genetic analysis of cancer, but it is also important to grasp the practical implication that arises from it. We must be able to discern how such analysis influences disease progression.


We hope you feel better prepared to give clear and concise answers during your next interview to become a cancer data scientist. Keep up with NCI data science career opportunities through our Jobs & Fellowships news category. We wish you luck as you work hard to strengthen your career trajectory!
Daoud Meerzaman, Ph.D.
Computational Genomics & Biomedical Informatics Branch Chief, Center for Biomedical Informatics and Information Technology
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That was really a great post. Thanks for sharing the information. Waiting for another.
Thank you for the feedback, we appreciate you letting us know that this type of content is useful for you! If you want to be sure you don’t miss future blogs like this, consider subscribing to our weekly email:
Great post. I must say you have provided us such useful and productive content.
We’re glad you found this blog useful. Please feel welcome to share it with any of your friends or colleagues who may find the content helpful!
Thanks Daoud! This gives me new ideas to add to my questionnaire which I use while assessing candidates for our open positions.
That’s great that you’ll be able to use this blog for adding to your questionnaire; we’re glad you found the content so helpful! We’ll be sure to let Daoud know you appreciated his work on this blog.