Brex Data Scientist Interview Questions

1.Tell me about a data problem you noticed that wasn't on your team's roadmap — something nobody assigned to you. What did you do with it?

2.Walk me through a memo, design doc, or analysis writeup you authored that actually changed what your team decided to do. What was in it, and how did it land?

3.Describe a time you noticed a metric or model your team relied on was subtly wrong — not broken, just systematically misleading. How did you handle it?

4.Tell me about a time you had data insights ready but held back from shipping a model or analysis because you weren't convinced it was correct enough. What made you pause, and what did you do?

5.Tell me about a time you were pulled into a cross-team data problem — one where you had no formal mandate — and had to figure out what was actually going on and what to do about it. How did you navigate it?

6.Tell me about a time you wrote an analysis or proposal that stakeholders initially pushed back on hard. How did you structure your argument, and did you eventually change their minds — or change yours?

7.You're pulling spend transaction data from Snowflake to train a fraud detection model, and you notice the dataset has a significant class imbalance — maybe 0.1% of transactions are fraudulent. How do you handle that?

8.You have a Kafka topic streaming real-time card authorization events. Explain how you'd use that stream to build a near-real-time feature — say, 'number of transactions in the last 30 minutes for a given user' — to feed into a live scoring model.

9.We're trying to understand whether a new Brex Spend Management feature — automated expense categorization — is actually improving finance team efficiency. How would you design the experiment?

10.You've trained a credit limit recommendation model on historical Brex Card data. Six months into production, the product team says approval rates are fine but customers are reporting limits that feel too low. How do you diagnose what's happening?

11.Design a data pipeline that generates daily spend anomaly alerts for Brex Empower enterprise customers — flagging unusual spend patterns at the team or department level before a finance admin even notices. Walk me through the full architecture.

12.Brex is considering building a real-time credit limit adjustment system — limits update dynamically based on a company's live financial signals rather than a monthly batch review. What are the hardest statistical and systems challenges you'd have to solve?

13.We want to build a dashboard that shows Brex Card customers their predicted spend for the next 30 days, broken down by category. How would you design the underlying forecasting system?

14.Finance teams using Brex Spend Management often want to benchmark their company's spend against peers — 'are we spending more on SaaS than similar-stage companies?' How would you design the data system that powers that benchmarking feature?

15.We want to build a model that predicts which Brex Business Account customers are at risk of churning — closing their account or moving funds to a competitor — within the next 60 days. Walk me through how you'd design that system end to end.

16.Brex processes millions of card transactions per day. Design a system that learns and maintains a merchant category taxonomy — mapping raw merchant names to spend categories — that feeds into Brex Spend Management's expense reporting features.

17.Design a system that detects account takeover — someone other than the legitimate user making transactions on a Brex Card — in real time, without adding friction to legitimate cardholders. How would you approach this?

18.Brex sets credit limits for Brex Card customers, and those limits directly affect how much spend flows through the platform. Design a system that optimally allocates credit limits across the portfolio — balancing revenue, default risk, and customer growth — and explain how you'd measure whether it's working.

19.Think about a time you had to explain a complex data finding to a non-technical stakeholder — a product manager, finance lead, or exec. How did you decide what to include and what to leave out?

20.Describe a time you disagreed with a prioritization call your manager or team made about what data work to do. How did you handle it?

21.Tell me about a time you owned a data project that had a hard dependency on another team — engineering, product, or a data platform team — and that dependency started slipping. What did you do?

22.Describe a time you had to push back on a request to build or ship a model faster than you thought was safe, given the stakes of the use case. How did you make the case for slowing down?

23.Tell me about a time you identified that a team or company-wide data definition — something like 'active user' or 'revenue' — was being used inconsistently across teams and causing real problems. What did you do about it?

24.Tell me about a time a model or data product you owned had a production incident — something that surfaced a real customer or business impact. Walk me through how you ran the response and what you wrote up afterward.

25.Estimate the total annual revenue Brex earns from interchange fees on Brex Card transactions. Walk me through your assumptions.

26.The number of new Brex Business Account signups dropped 20% last week compared to the prior week. How do you figure out what happened?

27.Brex wants to send a targeted in-app nudge to customers who are underutilizing their Brex Card relative to their available credit limit — the hypothesis being they're routing spend to a competitor card. How would you define 'underutilization' and build the targeting logic?

28.We're seeing that Brex Spend Management customers who connect an accounting integration — like QuickBooks or NetSuite — have significantly higher 12-month retention than those who don't. How would you figure out whether the integration is actually causing retention, or whether this is just selection bias?

29.Brex is considering whether to extend credit limits to early-stage startups that have less than 6 months of banking history on the platform. Design a credit risk scoring approach for this segment where traditional financial signals are weak or absent.

30.Brex processes billions of dollars in card spend. Walk me through how you'd estimate the financial impact of a 1% improvement in automated expense categorization accuracy in Brex Spend Management — and how that should inform whether the ML team invests in improving the model.