Contentsquare Data Scientist Interview Questions
& Process

First, you'll have a 30-minute chat with a Talent Acquisition Partner about your background and career goals. Then, a 1-hour interview with a Data Science manager will cover job responsibilities, mutual internship expectations, your relevant experience, and a deep dive into a past significant data science project to check your technical skills. After that, you'll need to complete a remote exercise, an end-to-end data science project, to demonstrate skills aligned with the internship project qualifications. Depending on your performance, a follow-up discussion about your solution choices might be needed. Importantly, your Talent Acquisition Partner will provide video-call feedback after each stage, successful or not. I found the ContentSquare recruitment process to be very personalized and human, unlike other top-tech companies I've interviewed with. I highly recommend applying if you're interested in ContentSquare.

Applied for a senior data science role. The process started with a 15 min phone call with TAS. Then a 1 hour interview with the Head of Data Science. Then they were unsure about my seniority, so a 1 hour interview with an engineering manager. After this, I was told we could move forward, but the engineering manager apparently noticed I was not very enthusiastic. Then a home assessment. I sent back my work and a week later, I was told the DS team was happy and impressed about my work, but in the meantime, they had already hired 2 senior DS. They told me they would see if any role could match my profile. Finally, they might have had a role but still wanted to be sure about my seniority, so they proposed an interview with a DS research scientist and a software engineer. To tell me in the end that I did not fit their requirements. This process was awful.

I applied online, got contacted by one someone in their talent acquisition team. The process is as follows, 3 main steps: - Overview interview with a manager - Homework to do (in this case a Data Science kaggle like exercise, with free emphasis, you can either perfect the model, the data analysis or the productionizing, each part needs to be addressed) - Technical interview with Data Scientist about the homework + questions During the whole process you get feedbacks from the talent acquisition team, which is super nice. Be careful of the entry level they offer you, as it is really hard to get promoted when inside.