Hi Labs

Role: Data Scientist

College: MAS Batch, IIT Alum

Interview Date: Not Specified (Video published April 30, 2023)

Interview Type: Full-Time

Result: Selected

Difficulty: Hard (more difficult than other companies, LeetCode level 3/medium for DSA)

Rounds: 3 rounds (Test, ML Technical, Coding Technical, though only 2 technical rounds were given by the candidate)

Topics Asked: Machine Learning, Statistics, Aptitude, Dynamic Programming, Greedy Algorithm, GFG puzzles (gold puzzle, Monte Carlo simulation), variable sliding window, dynamic programming string question using DP, Projects, Internships, Deep Learning, Data Structures and Algorithms

Experience:

Jay Bhaskar, an alum of MAS Batch, shared insights into the Data Scientist interview experience at HiLabs.

Test Round:
The test included MCQs related to Machine Learning, Statistics, and Aptitude. There were also two coding questions; one involved dynamic programming, and the other used a greedy algorithm. The candidate completed all MCQs and one and a half coding questions.

Interview Rounds (2 rounds given):
The interview process involved three rounds, but the candidate only participated in two technical rounds, an ML technical round and a coding technical round, and did not have an HR round before selection.

ML Technical Round:
Questions were centered on projects mentioned in the resume and internships. Core machine learning concepts, statistics, and a combination of both were thoroughly covered.

Coding Technical Round:
This round included GFG puzzles such as the "gold puzzle" and "Monte Carlo simulation". Following the puzzles, LeetCode level three coding questions were asked, including a "variable sliding window" problem and a "dynamic programming string question using DP".

Tips and Suggestions:
Candidates are advised to be very proficient with Deep Learning, not just Machine Learning. Extensive practice on Data Structures and Algorithms (LeetCode level 3/medium) is crucial. Interviewers also look for out-of-the-box thinking to assess problem-solving skills. Candidates should be well-versed with their resume projects and internships, and comfortable discussing machine learning, statistics, and coding questions in their preferred language, mostly Python.