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Morgan Stanley interview notes, page 2 of 2

Large Enterprises

Screna has 17 Morgan Stanley interview write-ups. The most reported round is the technical phone screen (14).

17 interview notes · updated Sep 2026

Morgan Stanley·Software Engineer·Technical Phone Screen

Jun 2026
Morgan Stanley quant engineer interview where they go through your resume and pick a project to dig into. Pretty thorough, they want the full picture: the problem, your decisions, what you actually did versus the team.
  • Walk me through the projects on your resume. Pick one and explain the problem you were solving, the design decisions you made, the trade-offs involved, your specific contributions versus the rest of the team, what worked, what didn't, and what you took away from it.

“This is the kind of question that sounds easy until you're actually in it.”

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Morgan Stanley·Software Engineer·Online Assessment (OA)

Jun 2026
Got a geometry/line-coverage problem from Morgan Stanley, the kind that looks deceptively clean on the surface but has some real edge cases hiding underneath. No frills, just code.
  • Given n points on a 2D coordinate plane, find the minimum number of straight lines needed so that every point lies on at least one line.

“My first instinct was greedy: find the line covering the most uncovered points, mark them, repeat.”

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Morgan Stanley·Software Engineer·Technical Phone Screen

Jun 2026
Morgan Stanley software engineer interview that was basically one meaty dynamic programming problem. The question had enough edge cases to keep you busy for a while, and they wanted the full treatment: working solution, complexity analysis, and a follow-up optimization.
  • Given a non-empty string of digits, count the number of ways to decode it using the mapping 1→'a', 2→'b', ..., 26→'z'. Zeros can only appear as part of '10' or '20'. Implement an O(n) solution in C++, explain how you handle zeros and invalid states, analyze time and space complexity, and provide a space-optimized version.

“I knew this was a DP problem the second I read it, but the zeros tripped me up more than I expected.”

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Morgan Stanley·Software Engineer·Technical Phone Screen

Jun 2026
Morgan Stanley software engineer interview with a pretty meaty algorithms problem that had more layers to it than I expected. The question looked like a basic array problem but pulling apart the optimal strategy took a while to articulate clearly.
  • Given an array of positive integers, you can repeatedly pick any two numbers, pay a cost equal to their sum, and replace them with that sum until one number remains. What algorithm minimizes the total cost, why is it optimal, what are the time and space complexities, and can you implement it in C++? Also handle edge cases like a single element, duplicates, and very large integers.

“I knew a min-heap was involved pretty quickly but stumbled when asked to actually prove why greedy works here.”

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Morgan Stanley·Data Scientist·Technical Phone Screen

Jun 2026
Interviewed for a Data Scientist role at Morgan Stanley and got hit with a pure math/logic puzzle that felt more like a quant interview than anything data science related. Wasn't expecting it at all.
  • A dog runs along the boundary of a unit circle at speed 4. You start somewhere strictly inside the circle and can move anywhere inside the disk at speed 1. If you reach the boundary at the same point and time as the dog, you're caught. Can you guarantee an escape, and if so, how?

“This wrecked me for a few minutes.”

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Morgan Stanley·Data Scientist·Technical Phone Screen

Jul 2026
Market risk and data science screen at Morgan Stanley. Four questions, two of them pretty involved quant problems and two that felt like they were testing whether you actually think or just memorize.
  • Design a stress-testing framework for WTI and Brent crude oil positions, covering marginal modeling, dependence structure, t-copula calibration and simulation, multi-day horizon aggregation, scenario generation (historical, hypothetical, conditional, reverse), and how you'd validate and communicate the framework's limitations.
  • Given two normally distributed random variables X and Y with variances and correlation rho, what is Var(X+Y) when they're independent, and when they're dependent? When is X+Y itself normally distributed?
  • Classic Monty Hall: three doors, one car, host always reveals a goat after your pick. Should you switch, and what are the probabilities for staying vs switching?
  • You have 8 identical-looking balls where exactly one is heavier. Using a balance scale at most twice, how do you always find the heavier ball?

“This was the bulk of the interview.”

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Morgan Stanley·Data Scientist·Technical Phone Screen

Jul 2026
Live coding screen for a Data Scientist role at Morgan Stanley. Two functions, both pretty standard, but they pushed on complexity and edge cases more than I expected.
  • Write an iterative factorial function in Python. Be ready to explain how a recursive version would work and compare the time and space complexity of both approaches.
  • Write a Python function that returns a list of squares for the first n integers. State clearly whether your list starts from 0 or 1, and handle edge cases like n = 0 and negative input.

“The implementation itself took maybe two minutes.”

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