Goldman Sachs Coding Questions 2025 - DSA Problems & Solutions

Practice 25+ Goldman Sachs placement paper coding questions with detailed solutions. Access Goldman Sachs OA coding problems, DSA questions in Java, Python, C++ for Goldman Sachs placement 2025-2026.

Goldman Sachs Placement Paper Coding Questions - Complete Guide

Practice with 25+ Goldman Sachs placement paper coding questions covering DSA problems, algorithms, and system design concepts. These questions are representative of what you’ll encounter in Goldman Sachs online assessment and technical interviews.

What’s Included:

25+ Coding Problems: Easy, Medium, and Hard level questions with solutions
Multiple Language Solutions: Java, Python, and C++ solutions
Time Complexity Analysis: Every solution includes complexity analysis
Goldman Sachs Focus Areas: Arrays, strings, trees, dynamic programming, math

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Goldman Sachs OA Coding Section Overview

Goldman Sachs Online Assessment Breakdown:

Section	Questions	Time	Difficulty	Focus Areas
Coding Test	2-3	60-90 min	Medium	Arrays, strings, DP, math, optimization

Languages Allowed: C, C++, Java, Python

Coding Problems by Category

Best Time to Buy and Sell Stock

Problem: Find maximum profit from buying and selling stock once.

Example:

Input: [7,1,5,3,6,4]
Output: 5 (buy at 1, sell at 6)

Solution (Java):

public int maxProfit(int[] prices) {
    int minPrice = Integer.MAX_VALUE;
    int maxProfit = 0;

    for (int price : prices) {
        if (price < minPrice) {
            minPrice = price;
        } else if (price - minPrice > maxProfit) {
            maxProfit = price - minPrice;
        }
    }
    return maxProfit;
}

Solution (Python):

def max_profit(prices):
    min_price = float('inf')
    max_profit = 0
    for price in prices:
        min_price = min(min_price, price)
        max_profit = max(max_profit, price - min_price)
    return max_profit

Time Complexity: O(n) | Space Complexity: O(1)

Two Sum

Problem: Find indices of two numbers that add up to target.

Example:

Input: nums = [2, 7, 11, 15], target = 9
Output: [0, 1]

Solution (Java):

public int[] twoSum(int[] nums, int target) {
    Map<Integer, Integer> map = new HashMap<>();
    for (int i = 0; i < nums.length; i++) {
        int complement = target - nums[i];
        if (map.containsKey(complement)) {
            return new int[]{map.get(complement), i};
        }
        map.put(nums[i], i);
    }
    return new int[]{};
}

Solution (Python):

def two_sum(nums, target):
    seen = {}
    for i, num in enumerate(nums):
        if target - num in seen:
            return [seen[target - num], i]
        seen[num] = i
    return []

Time Complexity: O(n) | Space Complexity: O(n)

Maximum Subarray (Kadane’s Algorithm)

Problem: Find contiguous subarray with largest sum.

Example:

Input: [-2,1,-3,4,-1,2,1,-5,4]
Output: 6 (subarray [4,-1,2,1])

Solution (Java):

public int maxSubArray(int[] nums) {
    int maxSoFar = nums[0];
    int maxEndingHere = nums[0];

    for (int i = 1; i < nums.length; i++) {
        maxEndingHere = Math.max(nums[i], maxEndingHere + nums[i]);
        maxSoFar = Math.max(maxSoFar, maxEndingHere);
    }
    return maxSoFar;
}

Solution (Python):

def max_sub_array(nums):
    max_so_far = max_ending_here = nums[0]
    for num in nums[1:]:
        max_ending_here = max(num, max_ending_here + num)
        max_so_far = max(max_so_far, max_ending_here)
    return max_so_far

Time Complexity: O(n) | Space Complexity: O(1)

Longest Substring Without Repeating

Problem: Find length of longest substring without repeating characters.

Example:

Input: "abcabcbb"
Output: 3 (substring "abc")

Solution (Java):

public int lengthOfLongestSubstring(String s) {
    Map<Character, Integer> seen = new HashMap<>();
    int maxLen = 0, left = 0;

    for (int right = 0; right < s.length(); right++) {
        char c = s.charAt(right);
        if (seen.containsKey(c) && seen.get(c) >= left) {
            left = seen.get(c) + 1;
        }
        seen.put(c, right);
        maxLen = Math.max(maxLen, right - left + 1);
    }
    return maxLen;
}

Solution (Python):

def length_of_longest_substring(s):
    seen = {}
    max_len = left = 0
    for right, char in enumerate(s):
        if char in seen and seen[char] >= left:
            left = seen[char] + 1
        seen[char] = right
        max_len = max(max_len, right - left + 1)
    return max_len

Time Complexity: O(n) | Space Complexity: O(min(m,n))

Product of Array Except Self

Problem: Return array where each element is product of all others (no division).

Example:

Input: [1,2,3,4]
Output: [24,12,8,6]

Solution (Java):

public int[] productExceptSelf(int[] nums) {
    int n = nums.length;
    int[] result = new int[n];

    result[0] = 1;
    for (int i = 1; i < n; i++) {
        result[i] = result[i-1] * nums[i-1];
    }

    int right = 1;
    for (int i = n-1; i >= 0; i--) {
        result[i] *= right;
        right *= nums[i];
    }
    return result;
}

Time Complexity: O(n) | Space Complexity: O(1)

GCD and LCM

Problem: Find GCD and LCM of two numbers.

Example:

Input: a = 12, b = 18
Output: GCD = 6, LCM = 36

Solution (Java):

public int gcd(int a, int b) {
    if (b == 0) return a;
    return gcd(b, a % b);
}

public int lcm(int a, int b) {
    return (a * b) / gcd(a, b);
}

Solution (Python):

def gcd(a, b):
    while b:
        a, b = b, a % b
    return a

def lcm(a, b):
    return (a * b) // gcd(a, b)

Time Complexity: O(log(min(a,b))) | Space Complexity: O(1)

Count Primes

Problem: Count primes less than n using Sieve of Eratosthenes.

Example:

Input: n = 10
Output: 4 (primes: 2, 3, 5, 7)

Solution (Java):

public int countPrimes(int n) {
    if (n <= 2) return 0;
    boolean[] isPrime = new boolean[n];
    Arrays.fill(isPrime, true);
    isPrime[0] = isPrime[1] = false;

    for (int i = 2; i * i < n; i++) {
        if (isPrime[i]) {
            for (int j = i * i; j < n; j += i) {
                isPrime[j] = false;
            }
        }
    }

    int count = 0;
    for (boolean prime : isPrime) {
        if (prime) count++;
    }
    return count;
}

Solution (Python):

def count_primes(n):
    if n <= 2:
        return 0
    is_prime = [True] * n
    is_prime[0] = is_prime[1] = False

    for i in range(2, int(n ** 0.5) + 1):
        if is_prime[i]:
            for j in range(i * i, n, i):
                is_prime[j] = False

    return sum(is_prime)

Time Complexity: O(n log log n) | Space Complexity: O(n)

Power Function

Problem: Implement pow(x, n) - calculate x raised to power n.

Example:

Input: x = 2.0, n = 10
Output: 1024.0

Solution (Java):

public double myPow(double x, int n) {
    long N = n;
    if (N < 0) {
        x = 1 / x;
        N = -N;
    }

    double result = 1;
    while (N > 0) {
        if (N % 2 == 1) {
            result *= x;
        }
        x *= x;
        N /= 2;
    }
    return result;
}

Solution (Python):

def my_pow(x, n):
    if n < 0:
        x = 1 / x
        n = -n

    result = 1
    while n > 0:
        if n % 2 == 1:
            result *= x
        x *= x
        n //= 2
    return result

Time Complexity: O(log n) | Space Complexity: O(1)

Square Root (Binary Search)

Problem: Find integer square root without using sqrt function.

Example:

Input: x = 8
Output: 2 (sqrt(8) = 2.828...)

Solution (Java):

public int mySqrt(int x) {
    if (x < 2) return x;
    long left = 1, right = x / 2;

    while (left <= right) {
        long mid = left + (right - left) / 2;
        long square = mid * mid;

        if (square == x) return (int) mid;
        if (square < x) left = mid + 1;
        else right = mid - 1;
    }
    return (int) right;
}

Solution (Python):

def my_sqrt(x):
    if x < 2:
        return x
    left, right = 1, x // 2

    while left <= right:
        mid = (left + right) // 2
        if mid * mid == x:
            return mid
        if mid * mid < x:
            left = mid + 1
        else:
            right = mid - 1
    return right

Time Complexity: O(log n) | Space Complexity: O(1)

Trailing Zeroes in Factorial

Problem: Count trailing zeroes in n!

Example:

Input: n = 25
Output: 6 (25! = ...000000)

Solution (Java):

public int trailingZeroes(int n) {
    int count = 0;
    while (n >= 5) {
        count += n / 5;
        n /= 5;
    }
    return count;
}

Solution (Python):

def trailing_zeroes(n):
    count = 0
    while n >= 5:
        count += n // 5
        n //= 5
    return count

Time Complexity: O(log n) | Space Complexity: O(1)

Climbing Stairs

Problem: Count ways to climb n stairs (1 or 2 steps at a time).

Example:

Input: n = 4
Output: 5 (ways: 1111, 112, 121, 211, 22)

Solution (Java):

public int climbStairs(int n) {
    if (n <= 2) return n;
    int prev2 = 1, prev1 = 2;
    for (int i = 3; i <= n; i++) {
        int curr = prev1 + prev2;
        prev2 = prev1;
        prev1 = curr;
    }
    return prev1;
}

Solution (Python):

def climb_stairs(n):
    if n <= 2:
        return n
    prev2, prev1 = 1, 2
    for i in range(3, n + 1):
        curr = prev1 + prev2
        prev2, prev1 = prev1, curr
    return prev1

Time Complexity: O(n) | Space Complexity: O(1)

Coin Change

Problem: Find minimum coins needed to make amount.

Example:

Input: coins = [1, 2, 5], amount = 11
Output: 3 (5 + 5 + 1)

Solution (Java):

public int coinChange(int[] coins, int amount) {
    int[] dp = new int[amount + 1];
    Arrays.fill(dp, amount + 1);
    dp[0] = 0;

    for (int i = 1; i <= amount; i++) {
        for (int coin : coins) {
            if (coin <= i) {
                dp[i] = Math.min(dp[i], dp[i - coin] + 1);
            }
        }
    }
    return dp[amount] > amount ? -1 : dp[amount];
}

Solution (Python):

def coin_change(coins, amount):
    dp = [float('inf')] * (amount + 1)
    dp[0] = 0

    for i in range(1, amount + 1):
        for coin in coins:
            if coin <= i:
                dp[i] = min(dp[i], dp[i - coin] + 1)

    return dp[amount] if dp[amount] != float('inf') else -1

Time Complexity: O(amount × coins) | Space Complexity: O(amount)

Longest Increasing Subsequence

Problem: Find length of longest increasing subsequence.

Example:

Input: [10,9,2,5,3,7,101,18]
Output: 4 ([2,3,7,101])

Solution (Java):

public int lengthOfLIS(int[] nums) {
    int[] tails = new int[nums.length];
    int size = 0;

    for (int num : nums) {
        int left = 0, right = size;
        while (left < right) {
            int mid = (left + right) / 2;
            if (tails[mid] < num) {
                left = mid + 1;
            } else {
                right = mid;
            }
        }
        tails[left] = num;
        if (left == size) size++;
    }
    return size;
}

Solution (Python):

import bisect

def length_of_lis(nums):
    tails = []
    for num in nums:
        pos = bisect.bisect_left(tails, num)
        if pos == len(tails):
            tails.append(num)
        else:
            tails[pos] = num
    return len(tails)

Time Complexity: O(n log n) | Space Complexity: O(n)

House Robber

Problem: Maximum money that can be robbed (no adjacent houses).

Example:

Input: [2,7,9,3,1]
Output: 12 (rob houses 0, 2, 4: 2+9+1)

Solution (Java):

public int rob(int[] nums) {
    if (nums.length == 0) return 0;
    if (nums.length == 1) return nums[0];

    int prev2 = 0, prev1 = 0;
    for (int num : nums) {
        int curr = Math.max(prev1, prev2 + num);
        prev2 = prev1;
        prev1 = curr;
    }
    return prev1;
}

Solution (Python):

def rob(nums):
    prev2 = prev1 = 0
    for num in nums:
        curr = max(prev1, prev2 + num)
        prev2, prev1 = prev1, curr
    return prev1

Time Complexity: O(n) | Space Complexity: O(1)

Edit Distance

Problem: Find minimum operations to convert word1 to word2.

Example:

Input: word1 = "horse", word2 = "ros"
Output: 3

Solution (Java):

public int minDistance(String word1, String word2) {
    int m = word1.length(), n = word2.length();
    int[][] dp = new int[m + 1][n + 1];

    for (int i = 0; i <= m; i++) dp[i][0] = i;
    for (int j = 0; j <= n; j++) dp[0][j] = j;

    for (int i = 1; i <= m; i++) {
        for (int j = 1; j <= n; j++) {
            if (word1.charAt(i-1) == word2.charAt(j-1)) {
                dp[i][j] = dp[i-1][j-1];
            } else {
                dp[i][j] = 1 + Math.min(dp[i-1][j-1],
                               Math.min(dp[i-1][j], dp[i][j-1]));
            }
        }
    }
    return dp[m][n];
}

Time Complexity: O(m×n) | Space Complexity: O(m×n)

Binary Tree Level Order Traversal

Problem: Return level order traversal of binary tree.

Solution (Java):

public List<List<Integer>> levelOrder(TreeNode root) {
    List<List<Integer>> result = new ArrayList<>();
    if (root == null) return result;

    Queue<TreeNode> queue = new LinkedList<>();
    queue.offer(root);

    while (!queue.isEmpty()) {
        int size = queue.size();
        List<Integer> level = new ArrayList<>();

        for (int i = 0; i < size; i++) {
            TreeNode node = queue.poll();
            level.add(node.val);
            if (node.left != null) queue.offer(node.left);
            if (node.right != null) queue.offer(node.right);
        }
        result.add(level);
    }
    return result;
}

Time Complexity: O(n) | Space Complexity: O(n)

Lowest Common Ancestor

Problem: Find LCA of two nodes in binary tree.

Solution (Java):

public TreeNode lowestCommonAncestor(TreeNode root, TreeNode p, TreeNode q) {
    if (root == null || root == p || root == q) return root;

    TreeNode left = lowestCommonAncestor(root.left, p, q);
    TreeNode right = lowestCommonAncestor(root.right, p, q);

    if (left != null && right != null) return root;
    return left != null ? left : right;
}

Time Complexity: O(n) | Space Complexity: O(h)

Number of Islands

Problem: Count islands in a 2D grid.

Solution (Java):

public int numIslands(char[][] grid) {
    int count = 0;
    for (int i = 0; i < grid.length; i++) {
        for (int j = 0; j < grid[0].length; j++) {
            if (grid[i][j] == '1') {
                dfs(grid, i, j);
                count++;
            }
        }
    }
    return count;
}

private void dfs(char[][] grid, int i, int j) {
    if (i < 0 || i >= grid.length || j < 0 || j >= grid[0].length || grid[i][j] == '0')
        return;
    grid[i][j] = '0';
    dfs(grid, i+1, j);
    dfs(grid, i-1, j);
    dfs(grid, i, j+1);
    dfs(grid, i, j-1);
}

Time Complexity: O(m×n) | Space Complexity: O(m×n)

Practice Tips for Goldman Sachs OA

Master Fundamentals

Arrays, strings, hash maps
Mathematical operations
Dynamic programming
Tree/Graph traversals

Focus on Clean Code

Goldman values code quality
Write readable, efficient code
Handle edge cases
Comment where needed

Time Management

25-30 minutes per problem
Read problem carefully
Test with examples
Optimize if time permits

Finance-Related Problems

Stock buy/sell problems
Interest calculations
Portfolio optimization
Risk assessment

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Practice Goldman Sachs coding questions regularly! Focus on arrays, mathematical operations, and dynamic programming. Goldman Sachs values clean, efficient code.

Pro Tip: Goldman Sachs interviews also test financial domain knowledge. Understand basic financial concepts along with coding.

Last updated: February 2026

Goldman Sachs Coding Questions 2025 - DSA Problems & Solutions

Goldman Sachs Placement Paper Coding Questions - Complete Guide

Goldman Sachs OA Coding Section Overview

Coding Problems by Category

Practice Tips for Goldman Sachs OA

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Goldman Sachs Coding Questions 2025 - DSA Problems & Solutions

Goldman Sachs Placement Paper Coding Questions - Complete Guide

Goldman Sachs OA Coding Section Overview

Coding Problems by Category

Practice Tips for Goldman Sachs OA

Related Resources

FAANG & Top Tech

Global Tech Companies

Indian Product Companies

Service-Based Companies

Big 4 Consulting

Investment Banks

Indian Banks & FinTech

Global Banks & Financial Services

Indian Conglomerates

Retail & E-commerce

Government & PSUs

Compare Companies