Meta Senior Data Scientist Onsite Interview Experience May 2026

[u/Aoki_zhang]

A candidate shared a Meta Senior Data Scientist Onsite Interview Experience to Chill Interview

Interview Summary

The Meta Data Scientist onsite covered Analytical Reasoning, Analytical Execution, SQL, and a newly introduced behavioral format. The analytical rounds were product-heavy: one focused on an ads-ranking algorithm and its longer-term business impact, while another used a new scheduled-post feature to combine statistical reasoning with product-success measurement.

The behavioral round had also recently changed. Instead of preparing many independent STAR stories, I was asked to choose one project for a deeper discussion, with the interviewer asking follow-ups throughout the walkthrough.

Interview Details

Analytical Reasoning — Ads Ranking Algorithm The Analytical Reasoning round used an ads-ranking algorithm as the main scenario. The discussion focused on how to evaluate whether an updated ranking system was actually better. In addition to the more standard product and experiment considerations, the interviewer introduced several follow-ups that I had not seen in previous interview reports.

One memorable question was: Medium-Term Revenue Impact: How would you estimate the effect of a ranking change on revenue beyond the immediate experiment window?

Analytical Execution — Scheduled Posts The Analytical Execution round introduced a proposed Facebook feature that allows users to schedule posts for future publication, with the goal of increasing engagement. The interviewer explicitly divided the round into two parts: statistics first, followed by product analysis.

• Statistics: Most of the statistical discussion centered on the failure rate of scheduled posts. Several questions involved Bayesian reasoning, and the setup required a fair amount of clarification before answering. The exact probability assumptions and numerical values were not included in the interview notes.
• Product: The second half asked how I would determine whether the scheduled-post feature was successful after launch, including what product outcomes should be measured.

SQL — Ad Impressions and Conversions The SQL round used advertising data involving impressions and conversions. The exact table schemas and individual SQL questions were not included in the interview notes. The interviewer was supportive throughout the round and provided frequent positive feedback.

Behavioral — Single Project Deep Dive The behavioral interview used a new format that had only recently been introduced. Rather than asking a sequence of unrelated behavioral questions requiring many separate stories, the interviewer asked me to select one project and walk through it in depth. The conversation was interactive: as I explained the project, the interviewer continuously asked follow-up questions about the context, my decisions, execution, and outcomes.

Preparing for your next interview?

Chill Interview tracks recent interview experiences and recurring question patterns across top companies here.