Goldman Sachs vs Morgan Stanley: Interview Question Comparison

Preparing for technical interviews at top investment banks requires understanding their distinct patterns. Goldman Sachs and Morgan Stanley both assess core algorithmic skills, but their approach to question volume, difficulty distribution, and focus areas differs significantly. This comparison breaks down their technical interview landscapes to help you prioritize your preparation.

Question Volume and Difficulty

The most striking difference is the sheer volume of questions in their respective coding interview question banks.

Goldman Sachs presents a massive set of 270 questions, heavily weighted toward medium difficulty. The breakdown is approximately 51 Easy (E), 171 Medium (M), and 48 Hard (H) questions. This large pool suggests that while the fundamental concepts tested are consistent, interviewers at Goldman have a vast repository to draw from. Encountering a problem you've practiced verbatim is less likely, placing a premium on deep understanding and adaptability. The significant number of Hard questions indicates you must be prepared for complex, multi-step problems, especially for roles in their engineering divisions or quantitative strategies.

Morgan Stanley has a more focused set of 53 questions, with a difficulty distribution of roughly 13 Easy (E), 34 Medium (M), and 6 Hard (H) questions. The emphasis is clearly on medium-difficulty problems. This smaller, more curated bank suggests a higher probability of encountering a known problem or a close variant. Preparation here can be more targeted, but mastery of the core medium-level problems is non-negotiable.

Topic Overlap

Both firms test a nearly identical core set of data structures and algorithms, making foundational preparation efficient.

Common Core Topics: Array, String, Hash Table, and Dynamic Programming are explicitly listed for both. This reflects the industry standard for assessing a candidate's ability to handle data manipulation, efficient lookup, and optimization.

• Arrays & Strings: Expect problems involving traversal, two-pointer techniques, sliding windows, and sorting.
• Hash Tables: Crucial for achieving O(1) lookups and solving problems related to frequency counting, duplicates, and complements (like Two Sum).
• Dynamic Programming: A key differentiator for harder questions. You must be comfortable with classic patterns like knapsack, longest common subsequence, and pathfinding.

# Example: Two Sum (Hash Table) - Common at both firms
def two_sum(nums, target):
    seen = {}
    for i, num in enumerate(nums):
        complement = target - num
        if complement in seen:
            return [seen[complement], i]
        seen[num] = i
    return []

The main difference lies in the depth and breadth of exploration within these topics. Goldman's large question bank likely includes more intricate combinations (e.g., DP on strings or arrays with complex state) and a wider variety of problem patterns under the same topic headers.

Which to Prepare for First

Your preparation strategy should be sequential and cumulative.

Start with Morgan Stanley. Its focused 53-question bank, dominated by medium-difficulty problems, provides an excellent and manageable foundation. Mastering this set ensures you have a strong command of the core topics that are essential for both companies. Successfully solving these problems builds the confidence and muscle memory needed for more extensive study.

Then, tackle Goldman Sachs. Use the vast 270-question bank from Goldman to stress-test your foundational knowledge and expand your problem-solving repertoire. Treat it as an opportunity to encounter novel applications of the same core topics. The hard problems here will push your limits and prepare you for the most challenging scenarios at either firm. If you can perform well on a broad sampling of Goldman's questions, you will be over-prepared for the core technical challenges at Morgan Stanley.

In summary, build your foundation with the targeted Morgan Stanley list, then scale up your endurance and depth with the comprehensive Goldman Sachs set. This approach efficiently covers the shared technical core while preparing you for the full spectrum of difficulty.

For specific question lists and patterns, visit the Goldman Sachs and Morgan Stanley pages on CodeJeet.