LinkedIn vs ServiceNow: Interview Question Comparison

When preparing for technical interviews at major tech companies, understanding the specific patterns and expectations of each employer is crucial. LinkedIn and ServiceNow, while both requiring strong algorithmic problem-solving skills, present distinct interview landscapes in terms of volume, difficulty, and focus areas. This comparison breaks down their technical interview question profiles to help you strategize your preparation.

Question Volume and Difficulty

The data reveals a significant difference in the scale of documented problems for each company.

LinkedIn has a much larger public question bank, with 180 problems categorized by difficulty: 26 Easy, 117 Medium, and 37 Hard. This volume suggests a broader range of potential questions and a strong emphasis on Medium-difficulty problems, which constitute about 65% of their question set. The substantial number of Hards indicates that senior or more challenging roles will likely involve complex algorithmic thinking.

ServiceNow has a more focused public repository of 78 questions: 8 Easy, 58 Medium, and 12 Hard. The distribution is even more skewed toward Medium difficulty, making up roughly 74% of their questions. The lower total volume does not necessarily mean the interview is easier; it often indicates a more consistent and predictable question pattern centered on core computer science fundamentals. The lower count of Hard questions suggests a slightly less intense focus on extreme algorithmic optimization for most roles compared to LinkedIn.

Topic Overlap

Both companies heavily test foundational data structures. Array, String, and Hash Table problems are central to both LinkedIn and ServiceNow interviews. Mastering these is non-negotiable.

The key differentiator lies in their secondary focus:

• LinkedIn prominently features Depth-First Search (DFS), highlighting an emphasis on tree and graph traversal problems. Recursive and iterative navigation through connected data structures is a critical skill.
• ServiceNow shows a marked focus on Dynamic Programming (DP), indicating that problems involving optimization, counting, or "minimum/maximum cost" scenarios are common.

This divergence shapes the problem-solving mindset required:

• For LinkedIn: Be ready to model relationships (e.g., social connections, hierarchies) and traverse them using DFS, BFS, or union-find.

  PythonJavaScriptJava

  # Example DFS skeleton for a graph problem
  def dfs(node, visited, graph):
      if node in visited:
          return
      visited.add(node)
      for neighbor in graph[node]:
          dfs(neighbor, visited, graph)
  

• For ServiceNow: Practice breaking down problems into overlapping subproblems and building up solutions, often with tabulation or memoization.

  PythonJavaScriptJava

  # Example DP skeleton (tabulation)
  def dp_example(n):
      dp = [0] * (n + 1)
      dp[0] = 1  # Base case
      for i in range(1, n + 1):
          dp[i] = dp[i-1] + dp[i-2]  # State transition
      return dp[n]
  

Which to Prepare for First

Your preparation priority should be dictated by your interview timeline and the role's seniority.

Start with ServiceNow if you are earlier in your interview preparation journey or have an interview scheduled sooner. The smaller, more concentrated question set with a heavy Medium-difficulty focus allows for efficient, targeted study. Solidify Arrays, Strings, Hash Tables, and then drill deeply into Dynamic Programming patterns. This foundation is excellent and transferable.

Start with LinkedIn if you are preparing for a more senior role, have more lead time, or are already comfortable with core patterns. The vast question bank, higher count of Hard problems, and focus on graph traversal (DFS) require broader exposure and more practice time to handle unexpected problem variations. You must be adept at both foundational topics and complex graph algorithms.

In practice, a strong candidate will be well-versed in all the overlapping topics. The strategic difference is in where you allocate your deep dive time: into DP for ServiceNow or into DFS/Graphs for LinkedIn.

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