What shows up most at Meta
These are the question clusters that appear most often in the raw records and should shape how candidates allocate prep time.
SQL and data manipulation
44 mentionsCandidates frequently solve SQL queries, perform joins, aggregations, data cleaning, and use Python/pandas-style manipulations.
Product analytics and metrics
39 mentionsExpect questions on designing metrics, reasoning about KPIs, retention, growth analysis, and evaluating product performance.
Statistics and experimentation
28 mentionsInterviews test probability, statistics, causal inference, and A/B testing to assess analytical rigor and experimental thinking.
Where Meta puts the most pressure
The stage distribution tells candidates where the loop concentrates effort and what kind of reasoning tends to matter most in each round.
Phone Screen
63 recordsThe phone screen emphasizes practical SQL queries, Python manipulation, and basic product analytics questions to gauge foundational skills.
Onsite
55 recordsOnsite rounds focus on applying metrics reasoning, designing experiments, and solving complex product and notification use-case problems.
Technical Interview
17 recordsTechnical interviews test deeper statistical understanding, experimentation design, and algorithmic thinking in Python or SQL contexts.
Online Assessment
2 recordsThis stage appears in the dataset but does not yet have a richer written summary.
Outcome mix
What Meta usually signals
Representative questions from the visible record set
These examples help users understand the concrete question flavor without dumping the entire raw database into the public page.
What are the pros and cons of upranking shop ads?
How would you measure the success of upranking shop ads?
How would you design the algorithm for upranking shop ads?
How to determine if a notification is good or bad, and what data to use?
How to decide whether to launch a new notification that informs users about events their friends are attending?
How to find out if users are interested in a group video call using the provided table?
How to prepare for Meta
The prep layer should stay practical: what to review, which interview themes recur, and how GhostInterview fits the live round instead of just prep week.
Prep focus
Use GhostInterview during the actual interview
GhostInterview is not just for prep. Use it during live interview loops and follow-up pressure while the conversation is still happening. On supported platforms, the overlay is designed to stay hidden on screen share.
Related Interview themes
These are the recurring interview themes worth reviewing before a similar loop.
SQL
Meta relies on SQL challenges to assess candidates' ability to extract, transform, and analyze datasets effectively.
Data Manipulation
Python or pandas-style data manipulation exercises test practical data processing and cleaning skills.
Python
Python-based problem solving evaluates candidates' programming proficiency and ability to implement analytical solutions efficiently.
Open representative Meta records
This public page summarizes the pattern. The database is where users inspect the actual record detail, stage context, and full write-up.
2025(Apr - Jun) · Onsite · Rejected
Meta onsite record for a Data Scientist role that ended in rejected. Onsite record for Meta for a Data Scientist role. I will release the compilation of the four session…
Open in leaked questionsMeta Data Engineer, Product Analytics Interview Experience2025(Apr - Jun) · Phone Screen · Offer
Meta phone screen record for a Data Scientist role that ended in offer. Phone Screen record for Meta for a Data Scientist role. Last month I interviewed for Target E4 Du…
Open in leaked questionsMeta DSA E3 Seeking Help2025(Apr - Jun) · Onsite · Offer
Meta onsite record for a Data Scientist role that ended in offer. Onsite record for Meta for a Data Scientist role. Recently passed the DSA E3 interview, but I've heard…
Open in leaked questionsRelated GhostInterview pages
FAQ
What areas does Meta focus on in Data Scientist interviews?
SQL and data manipulation, product analytics and metrics, and statistics and experimentation are the most common areas.
Which interview stage is most frequent?
The Phone Screen stage is the most frequent, often assessing foundational SQL and analytics skills.
How important are product metrics questions?
Very important; they test your ability to reason about KPIs, retention, and growth, reflecting real product decision-making.
Do Meta interviews include coding in Python?
Yes, candidates are expected to manipulate data, implement analytical solutions, and handle datasets in Python.
Can GhostInterview help during the actual Meta interview?
Yes. Use GhostInterview during live coding rounds, system design discussion, and follow-up pressure while the interview is happening. On supported platforms, the overlay is designed to stay hidden on screen share.