Data Scientist applicants have rated the interview process at MITRE with 2.7 out of 5 (where 5 is the highest level of difficulty) and assessed their interview experience as 56% positive. To compare, the company-average is 65.3% positive. This is according to Glassdoor user ratings.
Candidates applying for Data Scientist roles take an average of 49 days to get hired, when considering 9 user submitted interviews for this role. To compare, the hiring process at MITRE overall takes an average of 29 days.
Common stages of the interview process at MITRE as a Data Scientist according to 9 Glassdoor interviews include:
Group panel interview: 24%
Phone interview: 21%
One on one interview: 17%
Presentation: 14%
Drug test: 10%
Background check: 7%
Skills test: 3%
Personality test: 3%
Here are the most commonly searched roles for interview reports -
I applied through a recruiter. I interviewed at MITRE (McLean, VA) in Jan 2022
Interview
Quick. Just two rounds, one where I gave a technical presentation about a topic of my choice, and the other with the hiring manager about company culture and benefits. For the technical presentation, be prepared to answer questions about the decisions you made, and the challenges you faced in building out the tool.
Interview questions [1]
Question 1
What challenges did you face in building this algorithm, and what were the broader impacts of your decision?
I applied online. The process took 2 months. I interviewed at MITRE
Interview
Had an initial webcam interview and then lengthy in-person, 2.5 hour panel interview with 6 plus people. Got asked a lot of questions about my data science experience, how I could help the company. Was told by the recruiter that they wanted to extend me an offer but were working on getting funding.
Recruiter kept ducking my calls and messages for almost three weeks after that, I had to call the main office to get a hold of him and they finally said they decided not to fund the position.
Really a waste of everyone's time.
Interview questions [1]
Question 1
Describe the difference between data science, analyst and engineer.
One round with my group leader over a phone call. Second with my department head talking about past project experience over a zoom call. It was a Not technical interview. If you already have the background it would not be super difficult if you’ve worked in the space or through curriculum.
Asked about my past projects on data science and the process. The process included ML models, cleaning and Explanatory data analysis. They seemed to be looking for something in particular in terms of subject matter.
Interview questions [1]
Question 1
Q: What is supervised learning? And give an example.