Four candidates describe Coursera data science interviews that started with a recruiter screen and, for some, ran four to seven weeks. They report SQL, statistics, A/B testing, causal inference and scheduling problems.
$154K
Avg. Base Comp
$183K
Avg. Total Comp
Not reported
Typical Rounds
4-7 weeks
Process Length
Four candidates who reported on Coursera's data science hiring all ended without an offer, and the recruiter screen is the stage they describe most often. One candidate was asked about background, motivation, scripting languages and work authorization. A senior-level candidate was asked why they were leaving their job and then got technical questions on causal inference and A/B testing. That candidate said the call ended before they could ask questions. Prepare concise spoken explanations of those topics, and bring your own questions in case time runs short.
One candidate who got further was told interviewers wanted to assess SQL, probability and statistics, including when to use logistic regression. They also had to walk through their resume and explain technical ideas to non-technical audiences. They found the depth and rigor inconsistent between rounds.
Timing and logistics were a recurring concern. One candidate reported a process of about four weeks. Another reported about seven weeks, with each round pushed back by roughly a week. A third reported a hiring-manager interview that was cancelled twice over about a month. Candidates described no-shows, email-only communication and unclear feedback. Confirm each interview in writing, keep a record of the schedule, and ask the recruiter what the remaining steps are.
These are individual accounts and may not match every team's process.
Synthesized from 4 candidate reports by our editorial team.
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Real interview reports from people who went through the Coursera process.
I went through Coursera's data scientist interview process expecting a straightforward technical screen, but the experience felt disorganized and frustratingly slow. The process stretched over seven weeks, and I met with more than ten people across multiple rounds. The first round was a phone screen with a recruiter where we covered basic background — my experience, why I was interested in Coursera, what scripting languages I use, and my work authorization status. That part felt fairly standard, though I noticed the interviewer seemed to be following a script pretty closely.
The subsequent technical and behavioral rounds were where things fell apart. In some sessions, interviewers appeared to be reading directly from a script without really engaging with what I was saying, which made the conversations feel hollow. I was asked to walk through my resume and tell them about myself, and there were questions about explaining technical concepts to non-technical audiences. The interviewers mentioned they wanted to assess SQL, probability, and statistics knowledge — concepts like when to use logistic regression. But the technical depth and rigor varied wildly between rounds, and I got conflicting signals about what they actually needed. Most frustrating was the pacing: each round got pushed back by about a week, so what should have been a three-to-four-week process dragged on indefinitely. By the end, the lack of momentum and the feeling that no one was fully invested made it hard to stay motivated. I didn't advance past the initial screening stages, and honestly, the disjointed process gave me serious doubts about how the team would operate day-to-day.
Prep tip from this candidate
If you interview at Coursera for a data science role, don't expect a polished process — prepare for SQL and statistical concepts like logistic regression, but be ready for inconsistency across rounds and significant delays. Focus on drilling SQL fundamentals and be able to articulate your reasoning clearly, since some interviewers may not be fully engaged.
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Synthesized from candidate reports. Individual experiences may vary.
Candidates report that the process typically opens with a recruiter call. One was asked about experience, interest in Coursera, scripting languages and work authorization. A senior candidate reports repeated questions about why they were leaving their job, followed by causal inference and A/B testing questions. That call may end without time for your questions.
One staff-level candidate describes moving from the recruiter screen to a hiring manager round that was cancelled or missed twice over about a month. The candidate was later told the team was moving forward with other candidates. This is a single report, so treat it as a possible risk and confirm times in writing.
One candidate reports being told interviewers wanted to assess SQL, probability and statistics, including when to use logistic regression. They were also asked to walk through their resume and explain technical concepts to non-technical audiences. They described the depth as inconsistent between rounds and some interviewers as script-driven. Prepare for both technical and communication questions.
Candidates report long loops in some cases. One described seven scheduled rounds across HR, product, marketing, sales, hiring peers and the hiring manager over about four weeks. Another reported meeting more than ten people over seven weeks, with rounds delayed by about a week each. Counts and timing varied, so ask the recruiter for your own schedule early.
