JPMorgan vs Expedia: Interview Question Comparison

When preparing for technical interviews at major companies, understanding their specific focus areas can dramatically improve your efficiency. JPMorgan and Expedia, while both requiring strong algorithmic skills, present distinct profiles in question volume, difficulty, and topic emphasis. This comparison breaks down their patterns to help you prioritize your study.

Question Volume and Difficulty

JPMorgan's question bank is notably larger and slightly more challenging overall. With 78 total questions, it provides a broader set of problems to study. The difficulty distribution (25 Easy, 45 Medium, 8 Hard) shows a strong emphasis on Medium-level problems, which are the core of most technical screens. The presence of several Hard questions indicates you may encounter complex scenarios, especially in later interview rounds.

Expedia's list is more compact at 54 questions, which can make focused preparation more manageable. Its distribution (13 Easy, 35 Medium, 6 Hard) also centers on Medium difficulty but with a slightly lower volume in each category. This suggests the interview process may be slightly less intensive in its pure algorithmic demands, though still rigorous.

Key Takeaway: JPMorgan requires preparation across a wider array of problems and a higher likelihood of encountering a challenging Hard question. Expedia's list, while still substantial, allows for deeper mastery of a smaller core set.

Topic Overlap

Both companies heavily test foundational data structures. Array, String, and Hash Table problems form the common core for both. These are essential for any interview prep.

The primary difference lies in their secondary focus:

• JPMorgan lists Sorting as a key topic. This often involves not just using a built-in sort, but implementing custom comparators, solving problems where sorting is the key insight (like "Kth Largest Element" or "Merge Intervals"), and understanding time/space complexity of sort operations.
• Expedia highlights Greedy algorithms. This points to problems where making a locally optimal choice at each step leads to a global optimum, such as "Task Scheduler," "Jump Game," or "Maximum Subarray."

This distinction influences the problem types you'll see most frequently.

# JPMorgan Focus: Custom Sorting (Python)
# Problem: Sort a list of intervals [start, end] by start time.
intervals = [[1,3],[8,10],[2,6],[15,18]]
intervals.sort(key=lambda x: x[0])
print(intervals) # [[1, 3], [2, 6], [8, 10], [15, 18]]

# Expedia Focus: Greedy (Python)
# Problem: Find minimum number of jumps to reach end (Jump Game II).
def jump(nums):
    jumps = 0
    current_end = 0
    farthest = 0
    for i in range(len(nums)-1):
        farthest = max(farthest, i + nums[i])
        if i == current_end:
            jumps += 1
            current_end = farthest
    return jumps

Which to Prepare for First

Start with the common core. Mastering Array, String, and Hash Table problems will build a foundation applicable to both companies. Practice high-frequency problems like Two Sum, Sliding Window, and Anagram checks.

If your goal is to interview at both, prepare for JPMorgan first. Its larger question bank and inclusion of Sorting covers more ground. The problem-solving patterns you develop for its Medium and Hard questions will naturally encompass the logic needed for many Greedy problems. Once comfortable with JPMorgan's list, reviewing Expedia's specific Greedy-focused problems will be a more targeted, efficient step.

If you are only targeting one company, tailor your deep dive accordingly: dedicate extra time to Sorting techniques and a wider variety of problems for JPMorgan, and drill down on canonical Greedy algorithms for Expedia.

For specific question lists and patterns, visit the company pages: JPMorgan Interview Questions and Expedia Interview Questions.