Pinterest Data and Business Analytics interview typically runs 7 rounds: HR, technical phone screen, and a 5-round loop. It usually takes a few weeks and includes multiple team leads plus a VP.
$145K
Avg. Base Comp
$186K
Avg. Total Comp
7
Typical Rounds
2-4 weeks
Process Length
We’ve seen Pinterest evaluate Data and Business Analytics candidates with a stronger technical lens than many people expect for a role that can sound business-facing on paper. In this experience, the early technical screen went well beyond a light check-in and pushed into domain-specific frameworks and policies, which is a good signal that Pinterest wants analysts who can speak credibly about the systems and rules behind the data, not just summarize metrics. That pattern matters: the company seems to care less about polished storytelling and more about whether you can reason precisely in the context of the product area you’ve worked in.
A recurring theme is the depth of the follow-up once an answer is given. Our candidate reported that interviewers dug in hard after each response, and the loop included fundamentals, security concepts, and a use-case grounded in the candidate’s own domain. That tells us Pinterest is looking for people who can defend their thinking under pressure and connect analysis to real operational constraints. The presence of a collaboration conversation and a VP-level competency discussion also suggests they’re checking whether candidates can work across teams and communicate with enough maturity to handle ambiguity.
The non-obvious takeaway is that this process can feel mismatched to the title if you assume a junior analyst interview will stay surface-level. It won’t. Candidates should expect deep technical probing tied to their past domain and be ready to explain not just what they did, but why their approach was appropriate in a specific policy, security, or product context.
Synthetized from 1 candidates reports by our editorial team.
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Real interview reports from people who went through the Pinterest process.
The process at Pinterest for the Data Analyst role started pretty conventionally, but the technical screen was a lot heavier than I expected. The HR round was mostly about my previous role, compensation, and standard questions around my domain experience, so that part felt straightforward. The phone screen technical round was where I realized not to underestimate it — they asked a lot of technical questions tied to my domain, including frameworks and policies, and it was more detailed than a typical quick screen.
After that came a loop of five rounds. Most of those were with team leads from different sister teams, which felt a little odd for a junior analyst role, but the questions themselves were fairly standard. They focused on fundamentals and security concepts, and they did dig in pretty deeply once I answered. There was also a collaboration round with standard behavioral questions to check how I work with others, a use-case round where I was given a problem based on my own domain and had to walk through how I’d solve it, and a competency round with a VP that was more leadership- and behavior-focused. Overall I wouldn’t call the process especially difficult, but the interviewer mix felt mismatched for the level. I didn’t get an offer, and my main takeaway was that the technical screen and the deep dives in the loop deserved more prep than I initially expected.
Prep tip from this candidate
Be ready for a technical phone screen that goes beyond basics into your domain’s frameworks and policies, and practice explaining security fundamentals clearly because the loop interviewers dug into those areas. Also prepare a concrete domain-specific use case story, since one round was a live problem-solving discussion based on my background.
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Sourced from candidate reports and verified by our team.
Topics based on recent interview experiences.
Featured question at Pinterest
How would you assess the validity of the result?
| Question | |
|---|---|
| Subscription Overlap | |
| Button AB Test | |
| Impression Reach | |
| Size of Joins | |
| Search Ratings | |
| P-value to a Layman | |
| Ad Comments | |
| WAU vs Open Rates | |
| Random Bucketing | |
| Amateur Performance | |
| Dice Rolls From Continuous Uniform | |
| Feed Impression | |
| Interquartile Distance | |
| Greater Release Dates | |
| A/B Testing a Checkout Button Change | |
| Overfit Avoidance | |
| New UI Effect | |
| Ranking Metrics | |
| Reward Experiment | |
| Maximum Common Substring | |
| Singly Linked List | |
| Statistically Significant Test | |
| Meaningful Session Calculation | |
| Video Pins | |
| Empty Neighborhoods | |
| 2nd Highest Salary | |
| Employee Salaries | |
| Top Three Salaries | |
| Rolling Bank Transactions |
Synthesized from candidate reports. Individual experiences may vary.
The process starts with an HR conversation covering your previous role, compensation expectations, and general questions about your domain experience. This stage is described as straightforward and mostly focused on background fit.
The technical screen is more detailed than a typical quick phone screen. Interviewers ask domain-specific technical questions, including frameworks and policies, and expect you to go deeper than surface-level answers.
Candidates then go through a loop of five interviews, often including team leads from different sister teams. The rounds cover fundamentals, security concepts, a collaboration/behavioral interview, a use-case problem based on your own domain, and a competency round with a VP focused on leadership and behavior.