Affirm interview questions

After I was referred by an Affirm employee, HR immediately reached out and was prompt in setting up two phone screens and the on-site interview. The phone screens involved basic programming questions, some of which I answered correctly and some of which tripped me up. The on-site interview involved two more programming-based interviews, an interview involving a deep dive into analyzing an Affirm-related dataset, and two more interviews regarding my past projects and core data science knowledge. Each of the interviewers was clear and respectful, and no one asked any trick questions or gimmicks. Virtually all the questions dealt with problems that Affirm itself faced (and not abstracted to the point of ludicrousness), which made the interviews feel very relevant. After receiving an offer, I discussed the potential position and team with the hiring manager at-length, which increased my confidence that joining the Affirm data science team would be the best option for me. Note that the process would have taken two weeks, but since I began interviewing around the end of the quarter (December) and had to deal with finals, I requested to have more time in-between interviews. HR was very accommodating of my situation and always got back to me promptly (thank you!).

Best experience I've ever had with an interview process! The recruiter I worked with was friendly, efficient, and ensured that I was kept in the loop throughout the entire process. Everyone I spoke with and/or met was on-time, thoughtful, and engaged. I applied online and the recruiter reached out the next day to schedule the first phone call. The process involved: 1) phone call with the hiring manager, 2) take-home analytics exercise, and 3) on-site interviews. The first phone call was behavioral and a business case. From what I gathered, the main objective of this conversation was to assess interest in Affirm, relevant skill sets/experiences, fit, and structured thinking when breaking down problems. The analytics exercise involved analyses of a few data sets (in Python, R, and/or SQL of my choosing) and a short presentation of findings. This was not just an assessment of technical ability, but equally as important, a glimpse into the types of data the team works with and the problems they tackle. The exercise is a great opportunity for candidates to ensure that the role/work is interesting to them. Lastly, on-site conversations were a mix of behavioral, business cases, and idea generation/brainstorming. Behavioral parts were focused on past projects/experiences and why I was interested in Affirm. The business cases and brainstorming parts were focused on real issues/questions that the team & company tackles everyday, e.g. how do we improve the product, improve funnel performance, acquire new customers, etc. The conversations were very intellectually stimulating, and everyone's passion for the mission and company was evident. Overall I had an extremely positive experience with the process!