Checkout.com Data Scientist Interview Questions
& Process

The hiring manager for the Data Analytics Team laid out how the team functions, its responsibilities and what it doesn't handle, and how data helps the commercial, merchant, and operations teams. This was to see if you can grasp complex ideas, deal with uncertainty, and think in terms of business stories instead of just looking at dashboards. Then, they talked about having an internal-consulting approach (like 'we provide the setup, not every single meal'), telling stories to executives, doing regular reports for leadership, and enabling self-service analytics. This checked for cultural fit, seniority, and if you're comfortable with sharing ownership rather than having total control. Lastly, they went over issues with data across different systems, data quality problems, and how strategies are changing. This was to check if you can handle messy, real-world data and think about solutions and long-term fixes instead of just quick patches.

Recruiter call, then a first round with a data scientist, followed by a take-home test. Didn't make it to the final round which had multiple interviews. The first round interviewer was a no-show and had to be rescheduled, which was okay but the reason given seemed like a lie. After submitting the take-home test (training an ML model), heard nothing for about a week. Finally told the test wasn't good enough, which was surprising as I'm pretty sure the model would work in the real world. Open to different approaches or missing something, so asked for feedback on what was lacking, but got no response. Overall, felt a lack of respect for candidates, which isn't a great sign.

There was an SQL test and then some questions about experiments and experiment design. Specifically, they asked about what kind of data and metrics to use, what tests to run, like single vs two-sided tests, and what statistical significance means.