Capital One Coding Questions 2025-2026 | Placement Interview Problems with Solutions

Capital One’s coding round assesses DSA and problem-solving for technology roles in banking and fintech. The process typically includes an online assessment (e.g. HackerRank) with 1–2 coding problems (medium focus) and possibly MCQs. Technical interviews extend to DSA, system design, and behavioral questions. They value clean code, optimal complexity, and clear communication.

Capital One Coding Round at a Glance

Format: OA (e.g. HackerRank) with 1–2 coding problems; technical rounds with DSA and possibly system design. Difficulty: Medium. Topics: Arrays, strings, trees, graphs, hash maps. Focus: Optimal solutions, edge cases, and communication.

Coding Questions - Complete Problem Set

Practice coding interview questions with solutions.

Arrays & Strings

1. Two Sum

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 []

2. Valid Parentheses

def is_valid(s):
    stack = []
    mapping = {')': '(', '}': '{', ']': '['}
    for char in s:
        if char in mapping:
            top = stack.pop() if stack else '#'
            if mapping[char] != top:
                return False
        else:
            stack.append(char)
    return not stack

3. Reverse String

def reverse_string(s):
    return s[::-1]

4. Palindrome Check

def is_palindrome(s):
    s = ''.join(c.lower() for c in s if c.isalnum())
    return s == s[::-1]

5. Merge Intervals

def merge(intervals):
    intervals.sort(key=lambda x: x[0])
    merged = []
    for interval in intervals:
        if not merged or merged[-1][1] < interval[0]:
            merged.append(interval)
        else:
            merged[-1][1] = max(merged[-1][1], interval[1])
    return merged

6. Maximum Subarray

def max_subarray(nums):
    max_sum = current_sum = nums[0]
    for num in nums[1:]:
        current_sum = max(num, current_sum + num)
        max_sum = max(max_sum, current_sum)
    return max_sum

7. LRU Cache

from collections import OrderedDict

class LRUCache:
    def __init__(self, capacity):
        self.cache = OrderedDict()
        self.capacity = capacity

    def get(self, key):
        if key not in self.cache:
            return -1
        self.cache.move_to_end(key)
        return self.cache[key]

    def put(self, key, value):
        if key in self.cache:
            self.cache.move_to_end(key)
        self.cache[key] = value
        if len(self.cache) > self.capacity:
            self.cache.popitem(last=False)

Company-Specific Focus Areas

Capital One often emphasizes arrays and strings (subarray, sliding window, parsing), trees and graphs (traversal, BFS/DFS), hash maps (frequency, two sum–style), and dynamic programming. Fintech context may show up in problem framing. Focus on time/space complexity, edge cases, and explaining your approach in interviews.

Related Resources

Interview Experience

Real interview experiences.

Preparation Guide

Complete preparation strategy.

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Practice these problems with emphasis on DSA, optimal solutions, and clear communication for Capital One’s process.

Last updated: February 2026