Uber, a global leader in ride-hailing, food delivery, and autonomous technologies, uses Uber OA to screen candidates for a wide range of roles, from software engineering to data science and operations. This comprehensive guide breaks down the Uber OA process, common question types, and offers actionable tips to help you succeed in this crucial stage of the hiring journey.
I. Uber OA Overview
1. Invitation and Platform
- Trigger: After submitting your resume, you’ll receive an OA invitation via email if your profile matches the role requirements. The assessment is typically on HackerRank or CodeSignal.
- Timeline: You usually have 5–7 days to complete the OA once you receive the invitation.
2. Test Structure
- Duration: 60–120 minutes, depending on the role.
- Sections:
- Technical Roles: Coding challenges, algorithm design, data analysis, system design.
- Non-Technical Roles: Behavioral questions, case studies, logical reasoning, data interpretation.
- Proctoring: Some OAs are proctored, requiring webcam on.
II. Core Question Types for Technical Roles
1. Coding Problems
(1) Route Optimization
- Example: Variation of the Traveling Salesman Problem (TSP).
- Skills: Graph algorithms, dynamic programming, heuristics.
(2) Data Streaming and Processing
- Example: Process real-time ride requests data (filter by location, time, preferences).
- Skills: Queues, asynchronous processing, Python libraries (Pandas, PySpark).
(3) System Design
- Example: Design a distributed ride-matching service (scalability, low latency, fault tolerance).
- Areas: Microservices architecture, load balancing, SQL vs NoSQL.
2. Algorithm & Data Structure Questions
- Topics: Sorting/searching (quicksort, binary search), tree/graph traversal (BFS, DFS), advanced structures (heaps, tries, hash tables).
- Sample: Calculate total fare per ride with discounts for long distances.
3. Data Science – Specific
- Machine Learning: Predict rider cancellation rates; evaluate classification algorithms.
- Data Analysis: Analyze Uber Eats orders trends; write SQL for top restaurants by volume.
III. Non-Technical OA Components
1. Behavioral Questions
- Focus: Alignment with Uber’s values (“Build Global & Impactful Products,” “Champion the Rider and Driver,” “Celebrate Boldness”).
- Samples:
- “Describe a time you made a difficult decision under pressure.”
- “Share an experience working in a diverse team.”
2. Case Studies & Logical Reasoning
- Operations: Solve driver shortage in a city; propose pricing model impacts.
- Product: Design an in-app tipping feature; analyze market trends and competitors.
IV. Real OA Questions & Solutions
Question 1: Coding
Task: Given ride requests with start, end, and distance, filter out requests > 50 miles.
ride_requests = [
{"start_location": "A", "end_location": "B", "distance": 30},
{"start_location": "C", "end_location": "D", "distance": 60},
{"start_location": "E", "end_location": "F", "distance": 25}
]
def filter_ride_requests(requests):
return [req for req in requests if req["distance"] <= 50]
filtered = filter_ride_requests(ride_requests)
print(filtered)Question 2: Behavioral
Prompt: “If you noticed a colleague using unethical methods to meet targets, what would you do?”
Answer: “I would first discuss privately. If unresolved, I’d escalate to management or ethics hotline to uphold integrity.”
Question 3: Data Science
Task: From tables rides(ride_id, driver_id, start_time, end_time) and drivers(driver_id, driver_name, rating), find drivers who completed > 10 rides in a month.
SELECT d.driver_name, d.rating
FROM drivers d
JOIN rides r ON d.driver_id = r.driver_id
WHERE EXTRACT(MONTH FROM r.start_time) =
GROUP BY d.driver_id, d.driver_name, d.rating
HAVING COUNT(r.ride_id) > 10;Need help? The Programhelp team offers coaching covering Coding, System Design, and Behavioral questions. Contact us to get interview-ready!
