
Figma Data Scientist Interview Questions
& Process
Real candidates share what happened, how many rounds they had,
and how the experience turned out.
Based on 12 interview experiences · FREE TO READ
Candidate interview experiences
First-hand accounts from people who interviewed at Figma.
Product Data Scientist
The tech screen had two interviews. One was Experimentation and the other was Coding. Coding was on Python functions/Data Science related and SQL moderate difficulty. I had cleared Meta on similar testing areas, did really well for Figma and was super confident to move to next stage but got a reject! No feedback shared. Disappointed.
- Tell me about A/B testing, metrics, and decision making in experimentation.
- Write Python functions for data science tasks.
- Solve moderate difficulty SQL problems.
Data Scientist Intern
The interview process included a two-hour asynchronous technical interview on Byteboard. It started with analyzing a product case and doing some SQL queries. Then, there were two Python coding questions and an open-ended one that required both coding and writing. The final stage was a general behavioral interview and a case study about adding a product feature and how to track its success.
- Regarding KPI measurement, would a larger sample size be necessary to detect a 2% increase versus a 5% increase?
Data Scientist
There were 4 rounds in total. The first round was led by a data science leader and was a behavioral interview. This round can be a hit or miss. The interviewer interrupted and talked over the candidate, asking for a different answer to the same question instead of following up or asking for clarification. It seemed like the interviewer was just checking boxes rather than digging into the candidate's experiences. It left a terrible impression. My recommendation to Figma is to find a more empathetic and experienced interviewer for this round.
No confirmed questions were included in this interview report.
Figma Data Scientist Interview Questions
Quoted word for word from Figma interview reports.
“Write Python functions for data science tasks.”
Read reports →“Can you explain what a p-value is?”
Read reports →“Regarding KPI measurement, would a larger sample size be necessary to detect a 2% increase versus a 5% increase?”
Read reports →“Describe how to set up an A/B test.”
Read reports →“Can you suggest ways to improve the optimization of your various SQL tables?”
Read report →“Solve moderate difficulty SQL problems.”
Read report →“Could you design a system similar to Figma but on a smaller scale?”
Read report →“How would you estimate the market opportunity for a new product feature?”
Read report →“Tell me about A/B testing, metrics, and decision making in experimentation.”
Read report →Formats, difficulty and experience
Across all 12 Figma interview reports.