Stripe Data Scientist Interview Questions
Practice the exact questions companies are asking right now.
Design an idempotent SQL ETL for late data
You own the daily_user_metrics fact table. Build an idempotent, rerunnable ETL that can be triggered for any date D and correctly handles duplicates, ...
Resolve conflicts and prioritize with stakeholders
Describe a specific time you had to juggle conflicting priorities from Risk, Sales, and Engineering on a payments analytics project. Use STAR with dat...
Diagnose and validate a ratio trend change
You are shown a weekly dispute_rate time series (disputes/succeeded_payments) that rises sharply, then partially reverts. Diagnose whether the change ...
Choose target customers and define success metrics
Stripe plans to launch “Instant Payouts+” for SMBs. How would you choose initial target customers and measure success? - Targeting: Propose a scoring ...
Write SQL to monitor weekly chargeback spikes
Write a single SQL query (PostgreSQL) to detect weekly chargeback spikes by country and industry. Week starts Monday (use date_trunc('week', ts) with ...
Design a hierarchical forecast for transactions
Stripe wants a country×industry daily GMV forecast for the next 90 days (2025-09-01 to 2025-11-29) using 3+ years of history. You have features: day-o...
Quantify impact without an A/B test
Stripe-like scenario: You ship a change aimed at increasing payment success rate for APAC merchants, but randomization is infeasible. In ≤6 analyst‑ho...
Describe a high-impact project via STAR
Using STAR, walk me through one project you led that measurably changed a core business metric. Include: Situation (company, product, date range), Tas...
Prioritize a 6-hour take-home effectively
You are given a take-home similar to the above with a suggested 6-hour limit but a scope that could take much longer. Describe, concretely, how you wo...
Plan an experiment to validate targeting impact
You produced a ranked list of merchants predicted to adopt Subscription. Design an experiment to validate business impact of targeting them with a sal...
Design a model for subscription adoption prediction
Predicting 60-Day Adoption of Subscription by Non-Subscription Merchants Context You need to predict which merchants who are not currently using the S...
Write SQL to detect recurring non-subscription users
You have two tables: merchant and transaction. Assume 'today' is 2025-09-01. Schema: merchant(merchant_id INT PK, merchant_name TEXT, country TEXT, cr...
Design metrics and write SQL for a case
Case: Measure the impact of outreach on subsequent purchases and diagnose anomalies. Define your primary metric and write SQL. Schema and tiny samples...
Compute power and interpret uplift metrics
A/B Test on Conversion: Powering, Inference, CUPED, Multiple Testing, and Clustering You are running a two-arm A/B experiment on a binary conversion o...
Evaluate a new product with experimentation
Evaluation Plan for a New Recommendation Module in a Commerce App Background You are asked to evaluate a new recommendation module for a commerce app....
Design a target‑user prediction system
Predicting 30‑Day Adoption of Product P for Budgeted Outreach Context You are tasked with building a model to prioritize user outreach for Product P. ...
Scope an open‑ended take‑home under constraints
Take‑Home Planning Prompt: Predict Target Users in 6 Hours Context You have a 6‑hour take‑home assignment to plan how you would predict a product’s ta...
Navigate an ambiguous take-home assessment
Behavioral Case: Executing a 4–6 Hour Take‑Home Data Science Assignment Context You are a candidate for a Data Scientist role. You receive a one‑week ...
Implement streaming per-user reservoir sampling
Design and code (in Python) a streaming algorithm that ingests an unbounded event stream of tuples (user_id, event_time, event_type) and maintains, fo...
Choose threshold under costs and uncertainty
Incentive Targeting: Threshold Selection, Uncertainty, Calibration, and Drift Context: You deploy a model that sends an incentive to predicted positiv...