Machine Learning Interviews: Kickstart Your Machine Learning and Data Career

As machine learning professionals are increasingly in demand across tech companies, the interview process for these roles can be unpredictable due to varying responsibilities and skill requirements. Susan Shu Chang, a data science leader with experience as both interviewer and interviewee, provides guidance on navigating ML hiring. The guide covers how to explore different machine learning roles—including ML engineer, applied scientist, and data scientist—and assess which positions align with your interests and skills. It addresses how to evaluate your current abilities and identify gaps that may affect interview performance. Chang shares lessons learned from her experience as a principal data scientist at multiple companies. The guide explains how to build the necessary skill sets for each role and prepare for common ML interview components: coding assessments, statistics and machine learning theory questions, and behavioral questions.