Uber Data Scientist Interview Questions

1.Describe a time when you had to deliver insights or a model under tight deadline pressure. How did you balance speed with accuracy?

2.Tell me about a time you had to ship an analysis or model quickly to support a critical business decision. What corners did you cut and why?

3.Tell me about a time you built a model or analysis that needed to handle data from multiple countries or regions. What challenges did you face with scale and how did you solve them?

4.Tell me about a project where requirements or priorities changed significantly midway through your analysis. How did you pivot?

5.Walk me through a time when data contradicted what your team or stakeholders believed about user behavior. How did you handle the situation?

6.Describe a model you built that needed to handle millions of events or transactions. What was your approach to managing that volume?

7.You're building a demand forecasting model for Uber Rides to help with driver positioning. How would you incorporate external data sources and handle prediction uncertainty?

8.Explain how you would measure the success of a new feature that allows riders to add multiple stops to their trip. What metrics would you track and why?

9.You notice that Uber Eats delivery time predictions are consistently off by 15+ minutes in certain neighborhoods. Walk me through your debugging and solution approach.

10.Design an experiment to test whether showing estimated earnings to drivers before they accept rides increases driver acceptance rates. What are the key statistical considerations?

11.You're tasked with building a dynamic pricing model for Uber Rides that adjusts prices in real-time based on supply and demand. How would you approach the feature engineering and model architecture?

12.We need to detect fraudulent trips in real-time to protect both riders and drivers. Design a fraud detection system that can process millions of trip events per day.

13.Design a real-time ranking system that decides which drivers to show riders when they request a trip. The system needs to handle 50 million trip requests per day with sub-second response times.

14.Design an experimentation platform that can run thousands of concurrent A/B tests across Uber's global operations while handling network effects between riders and drivers in the same market.

15.We need to build a feature that predicts restaurant prep times for Uber Eats orders in real-time. Design a system that can handle predictions for 100,000 restaurants across different cities with varying order volumes.

16.Design a recommendation system for Uber Eats that suggests restaurants and dishes to users. The system needs to personalize for 50 million active users while handling cold start problems for new users and restaurants.

17.Build a surge pricing optimization system for Uber Rides that can adjust prices across thousands of city zones in real-time. The system needs to balance rider demand, driver supply, and revenue while maintaining fairness.

18.Design a machine learning system that detects and prevents account takeovers across Uber's platforms in real-time. The system needs to protect both rider and driver accounts while minimizing false positives that could block legitimate users.

19.Tell me about a time when you had to convince a product manager or engineering team to prioritize a data science initiative that wasn't originally on their roadmap.

20.Describe a situation where you had to lead a cross-functional team through a data science project when you weren't the formal project manager.

21.Walk me through a time when you had to make a significant change to how your team operated or approached a problem, and some people were resistant to that change.

22.Tell me about a time when you had to deliver difficult news or push back on unrealistic expectations from senior stakeholders about a data science project.

23.Describe a time when you had to build consensus among stakeholders who had fundamentally different views about what a data science project should optimize for or achieve.

24.Tell me about a time when you had to develop someone on your team or in your organization who was struggling with their performance or growth.

25.Estimate how many rides Uber would lose in San Francisco if surge pricing increased the minimum fare from 2x to 3x during peak hours. Walk me through your calculation.

26.You're analyzing driver churn in Mexico City and notice that 40% of new drivers stop driving within their first month. How would you investigate the root causes?

27.Uber Eats wants to expand grocery delivery to rural areas where order density is low. How would you estimate the minimum viable market size needed to make this profitable?

28.Driver utilization rates in Chicago dropped 8% month-over-month, but trip volume only decreased 3%. No major events or product changes occurred. How would you diagnose what's happening?

29.Design a model to predict which Uber for Business corporate clients are at risk of churning. The contract values range from $10K to $50M annually across different industries and company sizes.

30.Estimate the impact on Uber's global revenue if autonomous vehicles reduced trip costs by 30% but increased average trip distance by 20% due to changed user behavior.