Nasdaq Data Analyst interview typically runs 4 rounds: an emailed exam, three technical interviews, and one HR round. The process usually spans several stages and is notably exam-heavy and practical.
$71K
Avg. Base Comp
$138K
Avg. Total Comp
4
Typical Rounds
2-4 weeks
Process Length
We’ve seen Nasdaq evaluate Data Analyst candidates less like generalists and more like people who can step into a real workflow on day one. The strongest signal in the candidate experience is the exam-style work: the pre-interview assignment and the onsite exercise both felt like previews of the job, not abstract screens. That matters because the company seems to care about whether you can handle repetitive, operational analysis without losing accuracy or speed. One candidate specifically noted that the exercise gave a realistic sense of the day-to-day tasks they’d be expected to own.
A recurring theme is how much weight Nasdaq puts on the candidate’s own background. Interviewers dug into listed projects, then used those examples to branch into SQL, medium-level coding, and even OOP concepts, which tells us they’re looking for people who can explain decisions clearly under pressure, not just recite syntax. We also saw puzzle-style questions mixed in, so the bar isn’t purely analytics; it’s about whether you can reason through unfamiliar problems in a structured way. The technical bar felt solid but fair, especially for candidates who could connect their resume to practical outcomes.
One non-obvious pattern: the process can feel a bit uneven in communication, but the evaluation itself stays grounded in work realism. That combination suggests Nasdaq is optimizing for reliability and applied judgment. Our candidates report that the best fit is someone who can move comfortably between SQL depth, basic programming fluency, and clear project storytelling without sounding rehearsed.
Synthetized from 1 candidates reports by our editorial team.
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Featured question at Nasdaq
Design a database schema for a blogging platform.
| Question | |
|---|---|
| Subscription Overlap | |
| Prime to N | |
| Find the Missing Number | |
| Bank Fraud Model | |
| Hurdles In Data Projects | |
| Google Maps Improvement | |
| Fair Coin | |
| Radix Addition | |
| Find Duplicate Numbers in a List | |
| Target Indices | |
| Filling Supermarket Bag | |
| Median O(1) | |
| Assumptions of Linear Regression | |
| 5th Largest Number | |
| Implementing the Fibonacci Sequence in Three Different Methods | |
| Finding the Maximum Number in a List | |
| Check Matching Parentheses | |
| String Palindromes | |
| Confidence Interval Explanation | |
| Decision Tree Evaluation | |
| Your Strengths and Weaknesses | |
| Blob Indexing | |
| Client Solution Pushback | |
| Why Do You Want to Work With Us | |
| Singly Linked List | |
| Linear vs Logistic Regression | |
| Design Poker Schema | |
| Analyzing Multiple Data Sources | |
| Empty Neighborhoods |
Synthesized from candidate reports. Individual experiences may vary.
The process started with an initial recruiter phone call after the application. This stage was brief and served as an early check before the more technical parts of the process, though communication afterward was described as inconsistent.
Before the live interviews, Nasdaq sent an exam by email. It felt like a realistic preview of the role, focused on practical work rather than a generic screening test, and included tasks similar to the repetitive day-to-day work expected in the position.
There were three technical rounds in total, including one interview with a colleague abroad and one onsite conversation that also included an exam component. These interviews leaned heavily on the candidate’s resume, past projects, SQL questions, medium-level coding/problem-solving, OOP concepts, and some puzzle-style questions.
The final round was with HR and was more standard than the technical interviews. It focused on fit and general alignment rather than deep technical assessment.