Credit Sesame Data Scientist Interview Questions
& Process
Real candidates share what happened, how many rounds they had,
and how the experience turned out.
Based on 6 interview experiences · FREE TO READ
Candidate interview experiences
First-hand accounts from people who interviewed at Credit Sesame.
Credit Sesame
Data Scientist
Mid Average Negative experience No offer 3 rounds
Interview process
Recruiter call Phone screen Take home Offer
Interview formats
Behavioral Technical
Got an initial phone call with the recruiter, then a video call with the hiring manager. Got good feedback after that and was given a take home assessment. Finished the assessment but then didn't hear back for about 2 weeks. Finally got a response saying the results weren't good enough for the next step. Not sure what they were looking for since the assignment was a toy problem with no context. I tried to show the DS process, but apparently, they wanted someone to spend a lot of time on a technical skills assessment. They really need to re-evaluate their processes and be more considerate of candidates' time.
Confirmed questions1 question
- Tell me about typical Data Science questions, such as dealing with class imbalance, ranking systems, and recommendation engines.
Credit Sesame
Data Scientist
Mid Average Positive experience Decline offer 2 rounds
Interview process
Recruiter call Onsite
Interview formats
Behavioral Technical
I really enjoyed interviewing with Credit Sesame and learning about the role, team, and company! The interviewers were very smart and asked interesting and challenging, but in a good way, questions with no redundancy. I liked their bright office in a great Mountain View location with access to restaurants and a gym. Recruiter Phil was great – very responsive and kept me updated throughout. Ashlynn made me feel very welcome during the on-site. Based on the interviews, I believe Credit Sesame is a great place to work due to its culture and growth!
Confirmed questions2 questions
- Questions about the role
- Questions about cultural fit
Credit Sesame
Data Scientist
Entry Average Positive experience Accept offer 4 rounds
Interview process
Recruiter call Phone screen Technical screen Onsite Offer
Interview formats
Coding Technical Behavioral
Got an email from the recruiter about 8 days after applying on LinkedIn. Had a quick phone chat with the recruiter to ask some general questions about the company. Then, I had a more technical chat with someone from the data science team, mostly about standard ML concepts. Later that same afternoon, I was invited for an onsite interview. I met with four people there, including the CTO who leads the data science team. It was a good experience, everyone was friendly and the interviews went well. About 3 days after the onsite, I got a verbal offer over the phone. It was a really positive experience overall!
Confirmed questions4 questions
- Could you whiteboard some SQL that involves joining 3 tables?
- What are some ways to deal with imbalanced data in machine learning?
- Can you explain gradient descent in the context of machine learning?
Credit Sesame Data Scientist Interview Questions
Quoted word for word from Credit Sesame interview reports.
“Can you explain gradient descent in the context of machine learning?”
Read reports →“What are some ways to deal with imbalanced data in machine learning?”
Read reports →“Explain ML concepts simply.”
Read reports →“Can you discuss recommendation systems?”
Read reports →“Could you whiteboard some SQL that involves joining 3 tables?”
Read report →“Can you write some SQL queries?”
Read report →“Tell me about typical Data Science questions, such as dealing with class imbalance, ranking systems, and recommendation engines.”
Read report →“Tell me about your resume and past experience.”
Read report →Formats, difficulty and experience
Across all 6 Credit Sesame interview reports.