My Google Data Scientist Interview Experience in Hyderabad
A Challenging but Rewarding Journey
The Data Scientist interview process at Google in Hyderabad proved to be a multifaceted challenge, demanding both strong algorithmic problem-solving skills, system analysis proficiency, and effective communication. I wasn't actively seeking a new job, but when a Google recruiter reached out via LinkedIn for a Machine Learning Engineer (L4) position, I decided to take a shot. It felt like a great opportunity to assess my current capabilities.
In total, there were five interview rounds, encompassing a phone screen and onsite interviews.
Preparation involved about a month of dedicated study, including working through 250 LeetCode medium and hard problems, and reviewing Machine Learning theory.
Detailed Breakdown of Each Round
Round 1 – Phone Screen (DSA - Difficulty: 7/10)
45 minutes | Goal: Evaluate algorithmic thinking and clean coding.
Problem: Group strings that can be cyclically rotated into each other.
Input: ['abc', 'bca', 'cab', 'xyz']
Output: [['abc', 'bca', 'cab'], ['xyz']]
My approach: A straightforward brute-force method using a dictionary to store "normalized rotated" strings as keys, then grouping the corresponding strings.
Implementation went smoothly, and I explained time complexity and edge cases.
Feedback: Attention to edge cases needed improvement.
Result: Pass | Feedback: "Hire"
Round 2 – DSA 1: Advanced Topological Sort (Difficulty: 8.5/10)
60 minutes | Interesting topic: Deleting components of a storage system in a valid order.
Problem: Given a tree-structured storage system, determine the order in which to delete components without violating parent-child relationships.
Input:
A : [B, C]
B : [C]
C
D
→ Output: [D, C, B, A] or [C, D, B, A]
I implemented the topological sort algorithm using DFS. Success!
Follow-up: What if multiple components can be deleted simultaneously? Group them together.
Solution: Used BFS + a queue based on level to accomplish this.
Response: "Very impressive"
Result: Pass | Feedback: "Strong Hire"
Round 3 – DSA 2: Graph + Weighted Paths (Difficulty: 9/10)
60 minutes | Real-world problem, easy to mislead thinking.
Problem: Travel between countries using teleporters. Some teleporters are broken and require one day to repair. Find the optimal path from A to B with the lowest cost.
I used an adjacency list with weights (0 or 1 if the teleporter is broken).
Initially attempted BFS, but recognized it was inappropriate.
Switched to Dijkstra's algorithm, correctly calculating the cost to the destination.
Clearly explained time and space complexity and thoroughly commented the code.
Result: Pass | Feedback: "Strong Hire"
Round 4 – Googlyness & Leadership (Difficulty: 7/10)
45 minutes | Behavioral interview + storytelling skills.
Questions:
- Describe a time you gave difficult feedback that helped someone grow.
- What's a time you exceeded expectations in your job?
- What are your learning plans for the next year?
Result: Pass | Feedback: "Strong Hire"
Round 5 – ML Domain & System Design (Difficulty: 9.5/10)
60 minutes | In-depth interview about ML and system design.
Problem: Search for emails related to a query and personalize them according to user profiles.
I discussed designing a dual embedder model with a transformer.
Idea: Create embeddings for emails and queries, using cosine similarity for ranking.
However, when asked to implement a portion of the code, I froze because I forgot how to create tensors and set up an optimizer, revealing my reliance on ChatGPT.
The above is the complete interview experience of a member of the Leetcode community. What do you think of the questions in the Hyderabad rounds? Would you be confident in answering them well?
Collected information.
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