LinkedIn vs Visa: Interview Question Comparison

When preparing for technical interviews at top tech companies, understanding the specific patterns and expectations of each employer is crucial. Both LinkedIn and Visa ask challenging algorithmic questions, but their focus, volume, and difficulty profiles differ significantly. This comparison breaks down their question libraries to help you strategize your preparation effectively.

Question Volume and Difficulty

The raw numbers reveal distinct preparation scopes. LinkedIn's tagged question pool is larger, with 180 questions compared to Visa's 124. This suggests a broader range of problems you might encounter, requiring more extensive practice for LinkedIn.

The difficulty distribution is more revealing:

• LinkedIn (E26/M117/H37): The distribution is heavily weighted toward Medium difficulty (65% of questions), with a substantial number of Hard problems (21%). This profile is typical of major software-focused product companies, testing not just for correctness but for optimal solutions under constraints.
• Visa (E32/M72/H20): While also Medium-dominant (58%), Visa has a higher proportion of Easy questions (26% vs. 14%) and a lower proportion of Hard questions (16%). This indicates a slightly more accessible overall difficulty curve, though Medium problems remain the core of the interview.

In short, preparing for LinkedIn requires grappling with more Hard problems, while Visa's set, though still challenging, has a gentler ramp.

Topic Overlap

Both companies heavily test fundamental data structures. Array, String, and Hash Table problems form the absolute core for both, making these non-negotiable areas of mastery.

The key differentiator lies in the advanced topics:

• LinkedIn prominently includes Depth-First Search (DFS), a fundamental graph and tree traversal algorithm. This signals that recursive problem-solving, tree manipulations, and graph connectivity are in scope.
• Visa's additional noted topic is Sorting. This often involves problems that require arranging data as a primary step or leveraging sorted order (like two-pointer techniques on sorted arrays).

This divergence suggests LinkedIn interviews may involve more complex data structure relationships (trees, graphs), while Visa's problems might focus more on efficient data manipulation and organization.

# Example of a DFS pattern common at LinkedIn
def dfs(node, target):
    if not node:
        return False
    if node.val == target:
        return True
    return dfs(node.left, target) or dfs(node.right, target)

# Example of a sorting-based pattern common at Visa
def two_sum_sorted(nums, target):
    nums.sort()  # Sorting step
    left, right = 0, len(nums) - 1
    while left < right:
        current_sum = nums[left] + nums[right]
        if current_sum == target:
            return [left, right]
        elif current_sum < target:
            left += 1
        else:
            right -= 1
    return []

Which to Prepare for First

Your preparation order should be guided by a principle of foundations first, then specialization.

1. Start with the Shared Core: Begin by mastering problems involving Arrays, Strings, and Hash Tables at the Easy and Medium level. This builds the essential skills needed for both companies. Visa's question list, with its slightly higher Easy count, can be an excellent starting point for building confidence and speed.
2. Prepare for Visa as a Strategic Milestone: Given its strong core overlap and slightly more approachable difficulty distribution, targeting Visa-level proficiency first is a sound strategy. Ensure you are very comfortable with sorting algorithms and their applications (e.g., Arrays.sort, Collections.sort).
3. Then Level Up for LinkedIn: Once you are solid on the core and sorting, expand your preparation to tackle LinkedIn's specific demands. This means diving deep into Depth-First Search, tree traversals, and graph problems. Dedicate significant time to Medium and Hard problems to build the stamina and optimization skills their interviews require.

Effectively, preparing for Visa gets you ~80% of the way to LinkedIn's core requirements. The final 20% is an intensive push into advanced graph/tree algorithms and tougher problem variations.

For focused practice, visit the company-specific pages: LinkedIn Interview Questions and Visa Interview Questions.