
Gojek tech Data Analyst interview typically runs 4 rounds: phone screening, online HackerRank test, data scientist round, and manager round. It usually takes about 2-4 weeks and includes a notably long first test.
$150K
Avg. Base Comp
$243K
Avg. Total Comp
4
Typical Rounds
2-4 weeks
Process Length
Our candidates report that Gojek tech is looking for more than someone who can pull data and explain a chart. The strongest signal in the process is how deeply you understand experimentation: one candidate specifically called out in-depth A/B testing concepts and experimentation approach building, which suggests the team wants analysts who can reason through design choices, not just interpret outputs. We’ve also seen that the statistics bar can be surprisingly demanding for a Data Analyst role, with one experience describing the stats portion as difficult even when the SQL was only medium to hard.
A recurring theme is that Gojek seems to value analysts who can move comfortably between rigorous analysis and practical product thinking. The mention of advanced SQL topics like window framing points to a preference for candidates who can handle messy, real-world datasets and answer nuanced questions without hand-holding. In our view, the non-obvious make-or-break here is not raw technical breadth, but whether you can connect statistical judgment to product decisions in a way that feels precise and defensible. Candidates who do well here tend to sound like people who have actually thought through tradeoffs in experimentation, not just memorized definitions.
Synthesized from 1 candidate report by our editorial team.
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Topics based on recent interview experiences.
Featured question at Gojek tech
How would you investigate and address a decline in a model's production performance?
| Question | |
|---|---|
| Data Preparation for Imbalanced Data | |
| Statistically Significant Test | |
| Backpropagation Explanation | |
| Employee Salaries | |
| Experiment Validity | |
| Download Facts | |
| First to Six | |
| User Experience Percentage | |
| Button AB Test | |
| 500 Cards | |
| Weighted Keys | |
| P-value to a Layman | |
| Top 3 Users | |
| Third Purchase | |
| Average Order Value | |
| Raining in Seattle | |
| Maximum Profit | |
| Bank Fraud Model | |
| Encoding Categorical Features | |
| Impression Reach | |
| Daily Retention Summary | |
| Uber User Journey | |
| Lazy Raters | |
| Distance Traveled | |
| Bagging vs Boosting | |
| Network Experiment Design | |
| Revenue Retention | |
| Christmas Dinner Ingredient Optimization | |
| Google Maps Improvement |
Synthesized from candidate reports. Individual experiences may vary.
An initial phone screen to discuss your background, interest in the Data Analyst role, and overall fit for the team. This serves as the first filter before the technical rounds.
A timed online assessment focused on SQL and statistics. The SQL section was described as medium to hard, with advanced topics like window framing, while the statistics questions were notably difficult.
A technical interview with a data scientist covering experimentation and analytics fundamentals. Topics included A/B testing concepts in depth, advanced SQL, and how to approach building experiments.
A final round with the hiring manager to assess your analytical thinking, communication, and role fit. This stage likely focused on how you would apply experimentation and data analysis in the team’s work.