Fannie Mae Data Scientist interviews, as three candidates describe them, start with a recruiter or phone screen. Later rounds cover project walkthroughs, probability and statistics case questions, and in one account a take-home case study.
$140K
Avg. Base Comp
$167K
Avg. Total Comp
Not reported
Typical Rounds
4 months
Process Length
Three candidates describe Fannie Mae Data Scientist interviews, and they agree on one theme: be ready to explain your past projects in concrete detail. One candidate said project explanations took up much of the hiring-team conversation. Another said interviewers wanted proof that they understood the details of their own work.
The quantitative side comes up in several accounts. One candidate described a Zoom interview with two team members built around probability and math questions in a case format. They did not feel it was a SQL or Python coding test. Another said probability and statistics questions were woven through the process. A third said the technical portion was a few case questions, plus a question about which Python packages they had used. Practice talking through assumptions out loud, and be able to say what you actually did with each tool on your resume.
The format varied. One candidate had a take-home case study with a two-day window, followed by a virtual panel with leadership. In that panel they were asked how they would handle missing data in Python. Others described a recruiter or phone screen, then a combined behavioral and technical round with the team. One of those candidates also had a 45-minute session with a Data Science Principal. Outcomes were mixed: two candidates reported no offer and one reported an offer. Timelines differed too, and one candidate said their process ran about four months, so ask your recruiter about scheduling early.
Synthesized from 3 candidate reports by our editorial team.
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Real interview reports from people who went through the Fannie Mae process.
I didn't get an offer for the Data Scientist role at Fannie Mae, but the process was short and fairly predictable. It started with a phone interview that focused on why I was interested in the company. The next round was a combined behavioral and technical interview with the hiring team. The behavioral questions were the typical kind, but a large part of the conversation was about projects I had listed on my resume, so I'd expect them to ask you to walk through your work in real depth. The technical portion was a few case interview questions. One question I remember was simply which Python packages I had experience with, which made me realize how much they wanted to hear about my hands-on tools. Looking back, I'd spend more time preparing to explain my projects clearly than memorizing definitions, since that's where most of the time went.
Prep tip from this candidate
Be ready to walk through the projects on your resume in detail, since they took up a large share of the hiring-team round. Also have a clear answer for which Python packages you've used and what you actually did with them.
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Topics based on recent interview experiences.
Featured question at Fannie Mae
Design a RAG system that restricts LLM responses exclusively to ingested data, preventing use of pre-trained knowledge.
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Synthesized from candidate reports. Individual experiences may vary.
Candidates report an opening call with a recruiter that covers their background, why they want to join Fannie Mae, and what they want from the role. One describes it as a fit check rather than a technical round, so prepare a concise story of your experience and your interest in the company.
Candidates describe a conversation with the hiring manager or hiring team that mixes behavioral questions with discussion of past work. One says much of the time went to projects listed on their resume, so be ready to explain your decisions, methods, results and tools in detail.
One candidate reports a Zoom interview with two team members focused on probability and math questions in a case format. Another reports a few technical case questions and a question about Python packages. One candidate also reports a 45-minute analytical or statistical case study with a Data Science Principal.
One candidate who received an offer reports a take-home case study with two days to complete it. They describe it as a realistic work simulation instead of a live coding round. Not every candidate mentions this step, so confirm with your recruiter whether it applies to your process.
One candidate reports a final virtual panel with leadership-level interviewers. It focused on examples from past projects and how they handled challenges. It also included a question on handling missing data in Python, plus probability and statistics questions.
