I applied online. I interviewed at IBM (New York, NY) in Mar 2025
Interview
I interviewed at IBM NYC in March 2025. The interview process itself was pretty easy, recruiter screen, live coding, behavioral panel interview. I got offered three weeks later.
I joined as an Associate Data Scientist for the NYC office. Travel was mentioned, but I figured as a technical role I’d have some stability. In reality, our team was regularly sent all over the U.S. I spent weeks driving to client offices in NJ & CT, flying to Austin, Durham, and whatever IBM offices they needed the team. Felt like I was living out of a suitcase most of the year. It was tough to build any kind of routine, especially having to keep my utilization and hours logged to clients.
Leaving the company now after a year. Good resume builder, but not a career for me. Wouldn’t recommend to someone who is looking for stability.
Interview questions [1]
Question 1
Difference between gradient boosted trees and random forest
I applied online. I interviewed at IBM (New York, NY) in Mar 2026
Interview
OA has 1 sql question and 1 python question, both easy, administed via hackerrank, may be through another one though as well. you are given 60 mins to complete the OA portion of the interview process
Interview questions [1]
Question 1
You are given a table called Employee that contains each employee’s monthly salary and the number of months they have worked.
Find the highest total earnings among all employees
Determine how many employees have that exact highest earnings
I applied online. I interviewed at IBM in Jan 2025
Interview
first was an OA with 1 python (medium) 1 SQL (easy) question. Then had a technical on ML/DS trivia questions and concepts and then 1 easy python + 1 easy SQL question live coding. Final round was a behavioral with emphasis on the consulting / client facing side of the data scientist job. Ended up declining cause the job requires a ton of travel and I didn't want to do that unfortunately.
Interview questions [1]
Question 1
explain what is CNNs and RNNs and Attention Mechanisms and differences of each