Real, anonymous reports from people who interviewed for Data Scientist at Pinterest, newest first and distilled into what to expect across the loop.
After a recruiter touchpoint, I got a technical phone screen for the full-time data scientist role. It was a fairly tight, concrete setup: I answered two SQL questions and one Python question. The first SQL task asked me to find the top two categories by engagement rate per country, using event-style data like impressions and clicks joined with pin metadata. The Python question was centered on a “similar pins” style problem, where I worked through counting relationships between pin pairs.
My process started with an online coding assessment that ended up feeling brutal mostly because of how the tool environment constrained what I could do. The whole thing took about 70 minutes. It opened with seven multiple-choice questions that weren’t too bad, then moved into a LeetCode-style medium problem, and finally two ML-oriented coding problems that required building from scratch.
The online assessment typically consists of multiple-choice questions on machine learning concepts, followed by coding tasks that often include SQL and Python. Candidates should be prepared for a mix of easier and harder questions, with a strong emphasis on both theoretical knowledge and practical coding skills under time constraints.
Technical interviews often involve a combination of SQL, Python, and machine learning questions, with a focus on problem-solving and structured thinking. Candidates should expect to discuss their past work and demonstrate their analytical reasoning through case studies or scenario-based questions.
Coding challenges are typically framed in a LeetCode-style format, focusing on data structures and algorithms, with an emphasis on writing clean and efficient code under time pressure. Candidates should practice common algorithms and be ready to explain their thought process clearly.
Behavioral interviews assess cultural fit and teamwork, often incorporating questions about past experiences and how candidates handle challenges. Candidates should prepare to articulate their values and how they align with Pinterest's mission and culture.
The interview environment can vary from formal to conversational, with some rounds including multiple interviewers. Candidates should be prepared for a mix of direct questioning and collaborative problem-solving, as well as potential delays in scheduling.
Candidates often report a clear structure in the feedback process, but many do not receive offers despite feeling that they performed well. It's important to reflect on the experience and identify areas for improvement, especially in technical skills and interview preparation.