Meta Data Scientist Interview Questions

1.Tell me about a data science project where you had to deliver results quickly, even with incomplete information. How did you iterate after shipping?

2.Give me an example of when you had to quickly analyze data to support a time-sensitive decision. What shortcuts did you take and how did you validate your approach later?

3.Walk me through a time you proposed an unconventional data science approach that your team or leadership initially questioned. What was your reasoning?

4.How do you typically decide which data science projects to prioritize when you have multiple options? Give me a specific example.

5.Tell me about a time you had to share results or insights that your stakeholders didn't want to hear. How did you approach that conversation?

6.Describe a data science project where you specifically considered the social impact on users. How did that influence your approach?

7.Code a function that takes a stream of user engagement events and returns the top K most engaging posts in the last hour. Assume millions of events per minute.

8.Implement a data structure that efficiently tracks daily active users across different product surfaces at Meta scale. It should support adding user activity and querying DAU for any given day.

9.Walk me through how you'd design an A/B testing framework for a feature that affects both Facebook and Instagram users, considering that some users have accounts on both platforms.

10.You notice that your content ranking model for Facebook News Feed is performing worse for users in emerging markets. The overall engagement metrics look fine, but user feedback suggests the model isn't surfacing relevant content. How would you investigate and address this?

11.You're building a ranking model for Instagram Reels that needs to serve 500M users globally. The model training takes 8 hours but user engagement patterns change hourly. How would you approach this freshness vs. compute tradeoff?

12.You're tasked with building a machine learning model to detect coordinated inauthentic behavior across Meta's platforms. What features would you use and how would you approach this problem?

13.Design a real-time recommendation system for Instagram Stories that needs to personalize content for 500M daily users, where each user sees recommendations within 100ms of opening the app.

14.Design a data system to power Meta's Creator Fund payouts that needs to accurately track content performance across Facebook, Instagram, and emerging surfaces like Threads, while preventing fraud and ensuring payments are fair and timely.

15.You're building a data pipeline to detect and prevent coordinated spam attacks across Facebook, Instagram, and WhatsApp. How would you design a system that can process signals from all three platforms in real-time?

16.Design a feature importance and model interpretability system for Meta's content ranking algorithms that can explain to both internal engineers and external researchers why specific content was shown or not shown to users.

17.Walk me through designing a global feature store that serves ML features for Facebook News Feed ranking, Instagram Reels recommendation, and WhatsApp Business suggestions, with sub-10ms p99 latency across all Meta data centers.

18.You need to design a privacy-preserving analytics system for WhatsApp Business that can provide meaningful insights to business users about message engagement and customer interactions, while maintaining end-to-end encryption guarantees.

19.Tell me about a time you convinced a product manager or engineer to change direction based on your data analysis. What resistance did you face and how did you overcome it?

20.Describe a situation where you had to rally your team or cross-functional partners around a data science initiative that required significant effort but had uncertain outcomes.

21.Walk me through a time when you had to coordinate multiple teams to deliver a data science solution under a tight deadline. How did you ensure everyone stayed aligned?

22.Tell me about a time you identified that your team was working on the wrong problem or using the wrong approach. How did you redirect them?

23.Give me an example of when you had to advocate for a longer-term data science investment that didn't have immediate product impact but you believed was strategically important.

24.Describe a time when you had to lead through a major failure or setback in a data science project. How did you keep the team motivated and extract learning for the organization?

25.Instagram Reels engagement dropped 8% globally yesterday with no code deploys. Walk me through how you'd investigate this.

26.Estimate how many additional servers Meta would need if we doubled the video upload quality on Instagram Stories.

27.You need to estimate the revenue impact if WhatsApp Business increased message rates by 20%. How would you approach this?

28.Meta wants to understand why time spent in VR decreased 15% month-over-month despite Quest hardware sales growing. How would you investigate?

29.Design a framework to measure the social value created by Facebook Groups, considering both positive community building and potential harm prevention.

30.Estimate the computational cost if Meta implemented real-time fact-checking for every post across Facebook, Instagram, and Threads using current AI technology.