Ibm Data Scientist Interview Guide

IBM's Data Scientist interview, as candidates describe it, starts with an automated coding assessment before any person is involved. Most reports describe one SQL question and one Python question. Several call them easy, such as a join-and-aggregate query or a string-merging task. One candidate faced a harder algorithmic Python problem about peaks and troughs in an array. That candidate passed the visible tests, failed hidden ones and did not advance, so don't assume the Python question is always simple.

After the assessment, the next steps vary. One candidate was told by email that passing would lead to a recorded competency video answering a pre-recorded question, and another describes a competency interview after the coding round. One candidate also took a trait assessment. Candidates who advanced describe conversational rounds in which interviewers pick a project from the resume and keep asking why you chose a tool, how the pieces fit together, and how you protected data quality. One candidate reported applied ML and SQL questions with 30 minutes each. Another got a case-style question about using blockchain for medical records, where the interviewer cared about how the answer was structured.

Three candidates who reached later rounds received offers, while others were rejected after the assessment or a later round. Candidates also mention slow communication and little feedback. Prepare easy-to-medium SQL and Python, with some algorithm practice. Also prepare a project story you can defend decision by decision.