Goldman Sachs vs Accenture: Interview Question Comparison

When preparing for technical interviews at Goldman Sachs and Accenture, understanding the distinct focus and expectations of each firm is crucial for efficient study. Both assess core algorithmic problem-solving, but the scale, difficulty, and emphasis differ significantly, reflecting their unique business models. Goldman Sachs, a top-tier investment bank, evaluates candidates for high-performance, quantitative engineering roles, often in trading systems or risk platforms. Accenture, a global professional services and consulting giant, tests for robust problem-solving applicable to a vast array of client technology projects. This comparison breaks down their question profiles to guide your preparation strategy.

Question Volume and Difficulty

The data reveals a stark contrast in both the number of questions and their difficulty distribution.

Goldman Sachs (270 questions) presents a much larger and more challenging problem set. The difficulty breakdown is approximately 19% Easy (E51), 63% Medium (M171), and 18% Hard (H48). This profile indicates a rigorous interview process where mastery of Medium problems is the baseline, and the ability to tackle complex Hard problems is a key differentiator. The high volume suggests you may encounter a wider variety of problem scenarios.

Accenture (144 questions) has a more approachable distribution, with about 45% Easy (E65), 47% Medium (M68), and only 8% Hard (H11). This skew towards Easy and Medium problems aligns with a broader hiring funnel for consulting and technology roles where clear, logical thinking and implementation skill are prioritized over highly optimized, niche algorithms. The lower total volume also suggests a more focused core problem set.

Topic Overlap

Both companies heavily test foundational data structures, but with different depths.

Shared Core Topics: Array, String, and Hash Table problems are central to both. You must be proficient in manipulating these structures, performing searches, and implementing efficient lookups.

# Example: Two Sum (Hash Table)
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 []

Diverging Emphasis:

• Goldman Sachs prominently includes Dynamic Programming (DP). Expect questions on classic DP patterns (knapsack, longest common subsequence, coin change) which test optimization and state management for complex problems.
• Accenture lists Math as a primary topic. Focus on problems involving number properties, basic arithmetic, combinatorics, and mathematical logic, which are common in business application logic.

# Goldman Sachs focus: DP (Coin Change)
def coinChange(coins, amount):
    dp = [float('inf')] * (amount + 1)
    dp[0] = 0
    for coin in coins:
        for i in range(coin, amount + 1):
            dp[i] = min(dp[i], dp[i - coin] + 1)
    return dp[amount] if dp[amount] != float('inf') else -1

Which to Prepare for First

Prepare for Accenture first if you are early in your interview preparation journey or targeting both companies. Its emphasis on Easy/Medium problems on core data structures and math provides a solid, manageable foundation. Mastering this set will build your confidence and coding fluency for the majority of problems you'll see.

Once comfortable with the Accenture core, transition to Goldman Sachs preparation. This requires deepening your knowledge of Medium problems and dedicating significant time to mastering Dynamic Programming and Hard problem patterns. The Goldman Sachs problem set will test your limits on optimization and handling algorithmic complexity.

In summary, use Accenture's profile to build a strong foundation, then use Goldman Sachs' profile to push into advanced topics. The core skills from the former are directly transferable and necessary for the latter.

For specific question lists and patterns, visit the company pages: Goldman Sachs and Accenture.