LinkedIn vs Cisco: Interview Question Comparison

When preparing for technical interviews, understanding company-specific patterns is crucial for efficient study. LinkedIn and Cisco both assess core data structures and algorithms, but their approach differs significantly in volume, difficulty distribution, and focus areas. This comparison analyzes their question banks to help you prioritize your preparation.

Question Volume and Difficulty

LinkedIn's question bank is substantially larger and more challenging. With 180 total questions, its distribution is heavily weighted toward medium difficulty (M117, ~65%), with a significant portion of hard problems (H37, ~21%). This reflects LinkedIn's engineering bar and its focus on problem-solving depth, especially for senior levels (E26, ~14%).

Cisco's bank is smaller and less intense. With 86 total questions, it has a more balanced spread, though still medium-heavy (M49, ~57%). The proportion of easy questions is similar to LinkedIn (E22, ~26%), but it features far fewer hard problems (H15, ~17%). This suggests Cisco's interviews, while still rigorous, may place a stronger emphasis on foundational correctness and clarity over highly optimized, complex solutions.

Key Takeaway: Expect a longer, more difficult problem-solving session at LinkedIn. Cisco's interview might feel more standard, but don't underestimate it—medium problems still require solid preparation.

Topic Overlap

Both companies heavily test the absolute fundamentals: Array, String, and Hash Table are top topics for each. This is universal interview prep. Mastery here is non-negotiable for either company.

The primary divergence is in the next layer of focus:

• LinkedIn prominently lists Depth-First Search (DFS), indicating a strong emphasis on tree and graph traversal problems. Recursive and iterative backtracking are key skills.
• Cisco highlights Two Pointers, signaling a focus on in-place array/string manipulation, sliding windows, and problems where you track multiple indices.

This means your study plan should branch after covering the shared core.

# Example: Two Pointers (common for Cisco)
def reverse_string(s):
    left, right = 0, len(s) - 1
    while left < right:
        s[left], s[right] = s[right], s[left]
        left += 1
        right -= 1
    return s

# Example: DFS (common for 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)

Which to Prepare for First

Prepare for Cisco first. Its question bank provides a more manageable and focused roadmap. Mastering the core trio (Array, String, Hash Table) plus Two Pointers will build a rock-solid foundation. This covers a high percentage of their likely questions and is directly applicable to LinkedIn's fundamentals.

After conquering Cisco's core, scale up to LinkedIn. Use your established foundation and add deep, dedicated practice on DFS, tree/graph problems, and more complex medium/hard problems. The larger volume and difficulty of LinkedIn's bank means you should allocate significantly more study time.

Ultimately, preparing for Cisco first creates an efficient stepping stone. The skills are cumulative and transferable, making the jump to LinkedIn's more demanding profile less daunting.

For further details, explore the specific question lists for LinkedIn and Cisco.