ID Analytics Interview Questions
& Process

The interview process was quite thorough, with several stages. It began with a data challenge to assess skills in data cleaning and preprocessing using Python or R. This was followed by a 45-60 minute phone screen with a Data Scientist, covering past data science projects, basic statistics, and software engineering and ML fundamentals, all at a moderate difficulty focused on core knowledge. The next step was another 45-60 minute phone screen with a Sr. Data Scientist, delving deeper into machine learning algorithms and their constraints. Subsequently, there were four 45-60 minute panel interviews onsite at ID's San Diego office with team members, focusing heavily on technical aspects like ML, programming, stats, math, and MapReduce, plus a non-technical one-on-one with the hiring manager during lunch. The interviews were collaborative discussions, not interrogations, with helpful hints provided when needed. Overall, the experience was positive, with all interviewers being respectful and friendly.

I had a first easy phone screen with the recruiter. They asked questions to check my fit and skills for the job. It went well, so the recruiter set up a call with an engineering director. The next phone screen was mainly technical questions and some experience questions. The technical questions covered basic data structures and OOP. A few days later, the recruiter told me I passed and would have another technical phone screen with a manager. This person had a very strong accent, and I could barely understand anything. I asked them to repeat or slow down, but even then, I couldn't grasp what they were saying. For the questions I did understand, they weren't difficult, similar to the previous screen. The interviewer got upset because I kept asking them to repeat. I got an email a few days later saying I didn't pass.

HR reached out first, they seemed uninterested and asked about my background then read 2 technical questions. The next week, a very professional and technical person contacted me and asked a lot of technical questions. About two weeks after that, I was invited on-site to meet the team. They asked some probing questions, mostly to see if I’d be a good fit. It felt a bit disorganized overall, but it was alright.

People were friendly and mostly organized. The biggest stress was preparing for the case study. You are given a data file to analyze about goods sold in a fictional store, both online and in person and need to discuss your findings. The data file itself isn't too hard, but the panel evaluating your presentation includes director and VP level people, about a dozen or so sitting in.