Grammarly data scientist candidates describe a recruiter call, technical screens heavy on SQL and experiment interpretation, a virtual onsite with a product case, and culture or value conversations.
$189K
Avg. Base Comp
$285K
Avg. Total Comp
Not reported
Typical Rounds
Not reported
Process Length
Candidates describe Grammarly's data scientist interviews as practical and conversational rather than gotcha-driven. Each report begins with a recruiter call, and one adds a hiring manager conversation with technical discussion and case studies. One candidate describes a virtual onsite covering technical work, an experiment or A/B testing problem and a product case study, with no take-home assignment.
SQL is the most consistently mentioned skill. One candidate says the technical interviews leaned heavily on SQL, including a couple of dedicated SQL rounds, plus graph interpretation and business reasoning. Another describes data manipulation problems and SQL queries. Practice writing queries quickly and explaining your choices out loud.
Experimentation and data interpretation also come up. A candidate who interviewed for a senior role was asked to interpret graphs and explain what an experiment result does and does not show, and felt interviewers cared more about reasoning than recalling a specific formula. Another reports an A/B testing problem and statistics or ML questions tied to Grammarly's business. Practice talking through what a result supports and where its limits are.
Behavioral and project conversations matter too. Candidates mention reviews of past work, including where things went wrong and where they went well, plus cross-functional and value interviews. One candidate reports 10 or more conversations over several months and learning late that headcount had not materialized, so it may be worth asking your recruiter early about hiring status and timeline. Outcomes in these reports vary: one offer accepted, one offer declined and one rejection.
Synthesized from 3 candidate reports by our editorial team.
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Real interview reports from people who went through the Grammarly process.
Grammarly's interview process was genuinely thoughtful from start to finish. I started with a recruiter call, then moved into a hiring manager conversation that included some technical discussion and case studies. What struck me most was how carefully designed everything felt — the interviewers had clearly put effort into crafting questions that were practical rather than gotcha-style. The virtual onsite was the main event, spanning technical work, an experiment or A/B testing problem, and a product case study. Throughout, I worked through data manipulation problems, SQL queries, and questions around statistics and ML concepts that related directly to Grammarly's business. The whole team — especially the recruiter, who was exceptionally thoughtful and detail-oriented — came across as genuinely professional and welcoming. There were value interviews toward the end as well, where I could gauge fit and culture. The process took several weeks and covered quantitative skills, coding, business thinking, and soft skills without requiring any take-home assignments. Everyone was friendly and collaborative rather than adversarial. By the end, I felt like I'd had a genuine conversation with smart people who cared about finding the right fit, not just checking boxes. Ultimately I declined the offer, but the experience reinforced my sense that Grammarly treats both candidates and employees with real respect.
Prep tip from this candidate
Brush up on SQL problems involving joins across multiple tables and how to derive metrics from data. Be ready for product case studies and A/B testing scenarios grounded in Grammarly's actual product, and expect interviewers to engage collaboratively rather than interrogate — they value practical problem-solving over algorithm trivia.
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Sourced from candidate reports and verified by our team.
Topics based on recent interview experiences.
Featured question at Grammarly
How would you assess the validity of the result?
| Question | |
|---|---|
| Network Experiment Design | |
| Reward Experiment | |
| Scrapers or Users | |
| Length Of Longest Palindrome | |
| Empty Neighborhoods | |
| 2nd Highest Salary | |
| First to Six | |
| Top Three Salaries | |
| Upsell Transactions | |
| Longest Streak Users | |
| Last Transaction | |
| Rolling Bank Transactions | |
| Merge Sorted Lists | |
| Customer Orders | |
| Comments Histogram | |
| Closest SAT Scores | |
| Fair Coin | |
| Random SQL Sample | |
| Subscription Overlap | |
| Employee Salaries (ETL Error) | |
| Monthly Customer Report | |
| Top 3 Users | |
| 500 Cards | |
| Download Facts | |
| Find Bigrams | |
| First Touch Attribution | |
| Paired Products | |
| Raining in Seattle | |
| String Shift |
Synthesized from candidate reports. Individual experiences may vary.
Candidates report starting with a recruiter conversation about background, goals and fit. One candidate says the recruiter also sent materials on what to expect and how to prepare before the first technical screen, which may be worth requesting.
Candidates report a hiring manager conversation with some technical discussion and case studies, or a technical screen. Reported content includes SQL, data manipulation, graph interpretation and talking through experiment results. Interviewers are described as collaborative.
One candidate describes a virtual onsite spanning technical work, an experiment or A/B testing problem and a product case study, with SQL, statistics and ML questions tied to the business. Another reports dedicated SQL rounds. Exact format likely varies by team and level.
Candidates report conversations with people outside the immediate team, value interviews and reviews of past projects, including what went wrong and what went well. Be ready to walk through a project honestly and discuss collaboration.
Reported outcomes include an accepted offer, a declined offer and a rejection. One candidate reports a reference check late in the process and learning that headcount had not materialized, so asking about role status early may help.
