Morgan Stanley Data Analyst interview typically runs 3 rounds: HR screening, technical phone screen, and final hiring manager interview or superday. The process usually takes about a month and is fairly structured, with a mix of remote screens and live interviews.
$103K
Avg. Base Comp
$155K
Avg. Total Comp
4-6
Typical Rounds
3-5 weeks
Process Length
We've seen a recurring pattern at Morgan Stanley: the team cares less about flashy analytics and more about whether you can defend your own experience with precision. Multiple candidates said interviewers went line by line through their resumes, pushed for specifics on past projects, and kept circling back to why they wanted technology or analytics at Morgan Stanley. That tells us the bar is not just “can you do the work,” but “can you explain the work credibly in a finance setting.” Candidates who sounded polished but vague tended to struggle once the conversation turned to what they actually built, analyzed, or owned.
A second theme is the breadth of the technical screen. Our candidates report everything from SQL joins, ACID properties, and Python/pandas to Excel analysis, security basics, and even derivatives or LBO concepts. That mix is unusual for a Data Analyst title, but it fits a firm that expects analysts to operate comfortably around finance context and technical fundamentals at the same time. The strongest signal seems to be clear, practical reasoning: walking through an Excel sheet, explaining a query choice, or solving a simple coding problem without overcomplicating it.
What makes or breaks candidates here is often not difficulty, but range. Several experiences mention interviewers who were pleasant and conversational while still probing deeply, which means weak spots show up fast. We’d pay special attention to candidates who can connect data work to business outcomes, speak cleanly about market or financial concepts, and stay grounded when the questions shift from analytics into broader engineering or finance territory.
Synthetized from 6 candidates reports by our editorial team.
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Featured question at Morgan Stanley
Find the missing integer from a array of consequtive integers
| Question | |
|---|---|
| Size of Joins | |
| Sort Strings | |
| Assumptions of Linear Regression | |
| Implementing the Fibonacci Sequence in Three Different Methods | |
| Why Do You Want to Work With Us | |
| Your Strengths and Weaknesses | |
| Feedback Sentiment Analysis | |
| 2nd Highest Salary | |
| Empty Neighborhoods | |
| Rolling Bank Transactions | |
| Comments Histogram | |
| Employee Salaries | |
| Closest SAT Scores | |
| Top Three Salaries | |
| Slacking Employees Salaries | |
| Experiment Validity | |
| Compute Deviation | |
| Prime to N | |
| Bagging vs Boosting | |
| Last Transaction | |
| Department Expenses | |
| 500 Cards | |
| Session Difference | |
| Random SQL Sample | |
| Rain in N Days | |
| Subscription Overlap | |
| Paired Products | |
| Bank Fraud Model | |
| Hurdles In Data Projects |
Synthesized from candidate reports. Individual experiences may vary.
The process often starts with an HR screening call focused on background, motivation, and fit. Candidates are asked to walk through their resume, explain why they want the role, and why Morgan Stanley specifically.
Many candidates complete a HireVue with standard behavioral prompts, such as describing a setback or a conflict on a team. This stage is used to assess communication style and basic interpersonal fit before live interviews.
Candidates then move into a technical screen, sometimes with a software engineer or analyst. This round can include Python, SQL, data structures and algorithms, and fundamentals like ACID properties, joins, prime numbers, or Fibonacci.
A live interview with an analyst, associate, or managers on the team often mixes behavioral and practical technical questions. Candidates may be asked to go line by line through their resume, discuss Excel and financial modeling, or analyze an Excel worksheet and explain their thought process.
The final live round is often with one or two hiring managers and can be more hands-on. Depending on the team, candidates may code live, solve a medium LeetCode-style problem, answer broader technical questions, or discuss finance topics such as LBOs, merger models, derivatives, and market trends.
Some candidates report a structured virtual superday as the last stage, with conversations across multiple interviewers ranging from analysts to VPs or EDs. This round is conversational but rigorous, combining behavioral discussion, technical depth, and business judgment before the final decision.