Company Focus

Uber Interview Problems (45)

Problems reported from Uber data science interviews

Status Title Difficulty
Balancing Speed vs. Thoroughness Pro Easy
Batch vs Stream Processing Pro Easy
BFS vs DFS Pro Easy
Binary Search Requirements Pro Easy
Count Orders Per Status Pro Easy
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Filter Rows by Condition Free Easy
Filter Transactions by Amount Range and Date Pro Easy
Handling Ambiguous Requirements Pro Easy
Handling Missing Data Free Easy
Inner Join Orders and Customers Free Easy
Match Shippers to Orders Pro Easy
Multi-Table Join with Quantities Pro Easy
Stratified Sampling for Classification Pro Easy
Type I vs Type II Error Free Easy
A/B Test Duration Pro Medium
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Apache Kafka Use Cases Pro Medium
Cross Join for Combinations Pro Medium
Customers With No Orders in Last 90 Days Pro Medium
Experiment Design for Feature Launch Pro Medium
K-Means Clustering Limitations Pro Medium
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Learning Curve Diagnosis Pro Medium
Logistic Regression Assumptions Pro Medium
Merge Datasets Pro Medium
Model Deployment with Containers Pro Medium
RANK and DENSE_RANK Comparison Pro Medium
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