Morgan Stanley Campus Internship: Selection Process & Prep Guide

Morgan Stanley’s campus internship online test on HackerRank is 17 questions in 90 minutes: 7 quantitative aptitude MCQs, 8 DSA fill-in-the-blank questions, and 2 live coding problems.

No negative marking. That single fact changes test strategy entirely. Students who normally play safe on MCQ tests should attempt every aptitude question here.

Morgan Stanley in India: The Hiring Context

Morgan Stanley runs technology and operations functions in India primarily through Morgan Stanley Advantage Services (MSAS), headquartered in Mumbai with additional offices in Bangalore. Details about the India presence are on Morgan Stanley’s India page.

MSAS handles software engineering, financial operations, and technology infrastructure for the global firm. That means freshers who join are not doing generic IT services delivery. They work on systems that connect directly to Morgan Stanley’s global trading, investment banking, and wealth management operations.

The campus internship runs for six months. High-performing interns are considered for Pre-Placement Offers before their final year even begins. For students targeting this profile alongside other quant-driven technology companies, the D.E. Shaw campus recruitment guide covers a structurally similar process.

Selection Process: Four Stages

The typical campus internship drive runs in this sequence:

Stage	Format	Key Focus
Online Test	HackerRank, 17 questions, 90 min	Aptitude, DSA, Coding
Technical Interview 1	One-on-one	DSA depth, problem-solving approach
Technical Interview 2	One-on-one	CS fundamentals, project discussion
HR Interview	Discussion	Role fit, interest in finance-technology

The online test is the primary filter. Most rejections happen at this stage. Once past it, interview shortlists are smaller and the interaction is more substantive.

Online Test: Format and Section Breakdown

The test is hosted on HackerRank and covers three sections:

Section	Questions	Question Format	Topics
Aptitude	7	Multiple-choice	Quantitative mathematics
Data Structures and Algorithms	8	Fill-in-the-blank	Core CS data structures
Coding	2	Free-form programming	Algorithm implementation

Total: 17 questions. Time: 90 minutes. Negative marking: none.

For the coding section, C, C++, Java, and Python all qualify. The test scores correct algorithmic logic, not language preference.

Time management across the three sections matters. A useful rough split: 8 to 12 minutes for the 7 aptitude MCQs, 25 to 35 minutes for the 8 DSA fill-in-the-blank questions, and the remaining time for the 2 coding problems. Aptitude solved quickly buys the most time where it is hardest to recover.

The fill-in-the-blank format in DSA is worth understanding before the test. Rather than writing code from scratch, you complete code snippets. This tests reading comprehension of algorithms as much as it tests writing ability. Understanding what each line of a sorting or tree-traversal implementation does is as important as being able to write it independently.

Aptitude: Topics and Approach

The 7 aptitude MCQs test speed and accuracy in specific mathematical areas. Based on the test pattern, the coverage is:

• Permutations and Combinations: Arranging and selecting items from a set; basic counting principles using nPr and nCr
• Arithmetic and Geometric Progressions (AP/GP): Finding the nth term, calculating sum of a series
• Percentages and Proportions: Ratio reasoning, percentage change calculations
• SI Unit Conversions: Physics-based dimensional reasoning involving velocity, force, and unit analysis

A worked example from the P&C category:

• Q: In how many ways can 4 students be arranged in a row?
• Answer: 4! = 4 × 3 × 2 × 1 = 24 ways

The aptitude section rewards students who can solve problems in under 90 seconds each. Practice timed sets rather than open-ended problem-solving. Students who have drilled quantitative aptitude for analytics-focused drives can check the Mu Sigma aptitude test guide for overlapping topic patterns in P&C and series problems.

DSA and Coding: Where Shortlists Are Made

The DSA section carries 8 fill-in-the-blank questions. Topics that appear regularly:

• Arrays: sorting, two-pointer technique, in-place reversal
• Linked Lists: insertion, deletion, reversal logic
• Stacks and Queues: LIFO and FIFO operations, bracket-matching
• Trees: BFS, DFS, in-order, pre-order, and post-order traversals
• Graphs: adjacency representation, BFS and DFS traversals
• HashMaps: frequency counting, duplicate detection

The 2 coding problems follow the DSA section. Difficulty ranges from medium to moderately hard. Dynamic programming and recursion-based problems are common. Interviewers expect correct logic in a chosen language, not micro-optimised code.

Preparation order: master arrays and linked lists first, then trees, then graphs and DP. This sequence is also the correct build-up for the ZS Associates aptitude and interview process, where overlapping DSA depth is tested.

Interview Rounds: Technical and HR

Technical Interviews

The technical interview rounds probe DSA implementation in depth. After code is written, interviewers ask follow-up questions: What is the time complexity? Is there a better approach? How does this behave on edge cases?

Key areas tested:

• Data structures (trees, graphs, heaps, dynamic programming)
• Object-Oriented Programming: class design, inheritance, polymorphism
• Database Management Systems: SQL basics, normalisation concepts
• Operating Systems: process scheduling, memory management
• Computer Networks: HTTP, TCP/IP protocol basics

Projects discussed in Technical Interview 2 usually come from the academic portfolio or prior internship work. Being able to explain design decisions and limitations clearly carries more weight than listing technologies used.

HR Interview

HR questions at Morgan Stanley’s campus drives focus on fit for a finance-technology environment:

• Why Morgan Stanley over a pure-technology or IT services company?
• Describe a technical problem you solved without guidance.
• Where do you want to be in three years?
• What aspect of financial technology interests you?

Answers that reference specific operations or product areas of the firm read better than generic responses. The HR round is substantive, not a formality.

Six-Week Preparation Roadmap

Week	Focus	Daily time
1–2	DSA: Arrays, Linked Lists, Stacks, Queues	2 hours
3–4	DSA: Trees, Graphs, HashMaps, DP patterns	2 hours
5	Aptitude: P&C, AP/GP, Percentages, SI conversions	1 hour
6	Timed HackerRank mock tests and interview prep	2 hours

Start by benchmarking where you stand. A free diagnostic across aptitude, reasoning, and coding is available at the FACE Prep Campus Placement Evaluation Test.

For aptitude, focus on timed sets. Morgan Stanley’s test combines aptitude with DSA and coding in a shared 90-minute window, so speed in the aptitude section buys time for the coding problems.

For DSA, LeetCode medium problems in trees and graphs provide the right depth. Solving 80 to 100 problems across the topic list above before the drive gives adequate coverage for both the fill-in-the-blank section and the live coding questions.

For coding, practice on HackerRank specifically, since that is the platform Morgan Stanley uses. Familiarity with the interface removes friction on test day.

The 8 DSA fill-in-the-blank questions in Morgan Stanley’s test measure algorithmic precision at the implementation level, not surface recall. That same precision is what production AI engineering at financial-services scale requires. The student who prepares seriously for Morgan Stanley’s coding bar is already operating at the depth the programme expects.