The interview was a highly intensive, multi-hour process divided into several stages. It began with a 90-minute data challenge, requiring the candidate to define a target variable and build a model. Afterward, the candidate had to present their project in detail, facing questions about their choices, model, and results.
This was followed by individual technical interviews, where each interviewer focused on different topics such as logistic regression, decision trees, random forests, and deep learning. The questions were based on the candidate’s resume and the data challenge. Practical aspects like model training, deployment, and A/B testing were also discussed. Finally, a group session required the candidate to share a professional achievement, answer technical and product-related questions, and explain the rationale behind their work.
Interview questions [1]
Question 1
Why did you choose to define the target variable this way in the data challenge?
I applied through a recruiter. The process took 2 months. I interviewed at Intuit
Interview
Parts of the interview process were handled exceptionally (preparation for final round interview) and parts were handled extremely poorly (ghosted after a 6 hour final round interview).
They took over a month to schedule my final round interview. My initial interview was executed by someone who clearly did not want to be there and was abysmal.
I applied through an employee referral. The process took 2 months. I interviewed at Intuit (Mountain View, CA) in Oct 2023
Interview
First round was a phone screen with SQL questions, general ML and behavioural. I was given a take-home case study on MMM models. I spent days working on it which I had to present in the on-site round with the craft-demo presentation.