Bloomberg vs Infosys: Interview Question Comparison

When preparing for technical interviews, company-specific question patterns reveal what each organization prioritizes in their hiring process. Bloomberg and Infosys represent two distinct ends of the spectrum: a major financial technology and data company and a global IT services and consulting giant. Their publicly listed interview questions show clear differences in volume, difficulty, and focus, which directly shape how you should prepare.

Question Volume and Difficulty

The sheer scale of preparation differs drastically. Bloomberg's list contains 1,173 questions, dwarfing Infosys's 158. This volume indicates Bloomberg's process likely draws from a vast, well-documented pool of algorithmic problems, requiring broad and deep practice.

The difficulty distribution, based on community ratings, further highlights their different technical bars:

• Bloomberg (E391/M625/H157): The difficulty is weighted towards Medium and Easy questions, with a significant number of Hard problems. This suggests a strong focus on core algorithmic competency with some challenging problems to differentiate top candidates.
• Infosys (E42/M82/H34): The distribution proportionally mirrors Bloomberg's (roughly 1:2:0.5 for E:M:H), but with far fewer total questions. The emphasis is still on Medium-difficulty problems, but the overall scope is narrower.

The takeaway: Preparing for Bloomberg is a marathon of breadth and depth, while Infosys requires focused, efficient study on a more confined set of concepts.

Topic Overlap

Both companies emphasize Array and String manipulation, as these are foundational to most coding assessments. Math problems also appear for both, often involving number properties or basic computation.

The key difference lies in their secondary focuses:

• Bloomberg heavily features Hash Table questions. This aligns with real-time financial data processing, where efficient lookups and data association are critical. You can expect many problems involving mapping, counting, and caching.
• Infosys prominently lists Dynamic Programming (DP). This indicates a stronger emphasis on optimization problems and identifying overlapping subproblems, a common theme in complex system design and algorithmic efficiency for large-scale projects.

Here’s a simple example illustrating a common Hash Table pattern for Bloomberg versus a foundational DP pattern for Infosys:

# Bloomberg-style Hash Table: Two Sum
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 []

# Infosys-style DP: Fibonacci (memoization)
def fib(n, memo={}):
    if n in memo:
        return memo[n]
    if n <= 2:
        return 1
    memo[n] = fib(n-1, memo) + fib(n-2, memo)
    return memo[n]

Which to Prepare for First

Your priority depends on your target and timeline.

Prepare for Bloomberg first if: You are aiming for top-tier tech or fintech roles and have ample time (2-3 months). Mastering Bloomberg's list will force you to build exceptional breadth and solid problem-solving speed, which will make preparing for Infosys's more focused list feel like a subset review. The depth required for Bloomberg covers the core of what Infosys tests.

Prepare for Infosys first if: You are short on time, are new to technical interviews, or are specifically targeting IT services companies. Efficiently mastering the core Array, String, Math, and especially Dynamic Programming patterns in Infosys's list will build a strong foundation. You can then strategically expand into Hash Table and other common topics if adding Bloomberg-level companies to your target list later.

In essence, Bloomberg preparation is a superset of the skills needed for Infosys. Conquering the larger, more diverse list provides wider coverage, but targeted practice on the smaller list is the faster route to success for a specific interview.

For more detailed company-specific question lists, visit the CodeJeet pages for Bloomberg and Infosys.