Gusto Data Scientist candidates report recruiter screening followed by SQL-focused technical work; one 45-minute interview also paired SQL analysis with A/B-test interpretation and PM communication.
$195K
Avg. Base Comp
$268K
Avg. Total Comp
2 rounds
Typical Rounds
1-3 weeks
Process Length
Gusto Data Scientist interview reports point most clearly to practical SQL analysis paired with product-facing interpretation. One candidate described a recruiter screen followed by a SQL/Python round, where a date-based aggregation and a function for calculating elapsed days became a stumbling block. That makes it sensible to rehearse writing date logic from memory and to explain how you would validate an aggregation before finalizing it.
A separate candidate reported a single 45-minute session split between SQL in Deepnote and data analysis. Their SQL task used user and payroll data with aggregations and window functions. The analysis portion presented A/B-test results across multiple metrics, p-values, confidence intervals, and estimated effects; the candidate was asked to decide what the results meant and communicate a recommendation to a PM while accounting for uncertainty and tradeoffs.
Prepare to narrate your reasoning as you work: clarify the business question, state the metric or comparison you are using, and connect the conclusion back to a decision. Reports are limited, so the exact sequence and mix of topics may vary by team.
Synthesized from 3 candidate reports by our editorial team.
Had an interview recently?
Share your experience. Unlock the full guide.
Real interview reports from people who went through the Gusto process.
It was a single 45-minute interview split into two parts. The first part was SQL on Deepnote, followed by a data analysis exercise. Expect some time pressure, but remember it's a collaborative interview, the interviewer is happy to answer clarifying questions, and you're encouraged to think out loud. Focus on explaining your approach and connecting your analysis back to the business problem rather than trying to write the most optimized code.
Questions asked: The interview had two parts. The first was a SQL question where I analyzed user and payroll data using aggregations, and window functions.
The second part focused on experiment interpretation. I was given A/B test results with multiple metrics, p-values, confidence intervals, and estimated effect sizes, and asked to explain what the results meant, whether the experiment should be considered successful, and how I would communicate the findings to a PM. The emphasis was less on statistics (but you still need to understand the statistical test used) for its own sake and more on translating the results into clear product recommendations while acknowledging uncertainty and tradeoffs.
Share your own interview experience to unlock all reports, or subscribe for full access.
Sourced from candidate reports and verified by our team.
Topics based on recent interview experiences.
Featured question at Gusto
Write a query to get the total three-day rolling average for deposits by day
| Question | |
|---|---|
| Experiment Validity | |
| Top 5 Turnover Risk | |
| Customer Success vs. Free Trial | |
| Job Training Program Evaluation | |
| HR Salary Reporting | |
| Data Stream Median | |
| Why Do You Want to Work With Us | |
| Free Shipping Mention Test | |
| Empty Neighborhoods | |
| 2nd Highest Salary | |
| Customer Orders | |
| Top Three Salaries | |
| Comments Histogram | |
| Closest SAT Scores | |
| Merge Sorted Lists | |
| Subscription Overlap | |
| First to Six | |
| Monthly Customer Report | |
| Upsell Transactions | |
| First Touch Attribution | |
| Download Facts | |
| Compute Deviation | |
| Last Transaction | |
| Random SQL Sample | |
| Top 3 Users | |
| Employee Salaries (ETL Error) | |
| String Shift | |
| Button AB Test | |
| Bank Fraud Model |
Synthesized from candidate reports. Individual experiences may vary.
One candidate reports completing recruiter screening before a SQL/Python interview. No questions or duration for this conversation were provided, so applicants should treat it as an initial discussion rather than assume a defined evaluation format.
Candidates report SQL-focused technical work after screening, including a date-based aggregation problem and, in a separate 45-minute interview, analysis of user and payroll data using aggregations and window functions. Be ready to explain your query choices and recover if you forget syntax.
One candidate's 45-minute interview followed SQL with interpretation of A/B-test results containing multiple metrics, p-values, confidence intervals, and estimated effects. Candidates report being asked whether results were successful and how they would communicate findings to a PM, including uncertainty and tradeoffs.
