Capital One Interview Questions — Page 36

Capital One·Software Engineer·Online Assessment (OA)

Jul 2026

Capital One OA for a software engineering role. Four problems, ranging from pretty straightforward to genuinely tricky. The bubble explosion one ate up most of my time and I'm still not sure I got the gravity part right.

Given an array of positive integers and an integer k >= 1, count how many elements in the array are exact powers of k. Handle the edge case where k equals 1 separately.
On a planet where moon phases cycle every 8 days (indices 0 through 7), you're given the starting phase on day 1 and a list of month lengths for that year. For a given target date (month, day), compute the moon phase index on that date.
Simulate a bubble-explosion mechanic on an R x C grid: repeatedly find any 4-directionally connected group of the same color with size >= T, remove it (set to 0), then apply gravity so remaining cells fall to the bottom of their columns. Repeat until no more groups can be removed, then return the final grid.
Given an array of N numeric strings of equal length L (leading zeros allowed), count unordered pairs where one string can be transformed into the other using at most two character swaps within a single string. Analyze time and space complexity.

“This was the warmup and I almost tripped on the k=1 case.”

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Capital One·Data Scientist·Technical Phone Screen

Jul 2026

Capital One Data Scientist case interview focused entirely on a credit card profitability scenario. You build a revenue-cost model, compute per-user and portfolio-level profit, then evaluate whether a user-acquisition partnership pencils out financially.

Given the revenue and cost components of a credit card portfolio, calculate the current per-user profit and total portfolio profit.
If the company partners with an external institution to acquire new credit card users at a given cost per acquisition, is the partnership financially worthwhile?
Walk through a sensitivity analysis on the key assumptions driving the partnership decision.

“I started by listing out revenue streams (interchange, interest, fees) and cost items (credit losses, servicing, rewards) before touching any numbers.”

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Capital One·Data Scientist·Technical Phone Screen

Jul 2026

Capital One data scientist interview with a case-style question on weather insurance portfolio profitability. Mostly quantitative reasoning around breakeven math and segment selection. Not a coding round at all, which I didn't expect.

Using the given pricing and cost structure for a weather insurance product (monthly premium paid upfront annually, per-month servicing cost, a fixed benefit per claim, and regulatory costs that include both a quarterly flat fee and a per-claim charge), what claim rate per policy would put the portfolio at breakeven?
Four customer segments (A, B, C, D) each carry different cumulative claim risk profiles. Which combination of segments should you offer the product to in order to maximize portfolio profit, and what's the reasoning?
Starting from a baseline of only serving segment A, walk through how profit changes incrementally as you add segments B, C, and D one at a time.

“The math itself isn't that bad once you lay it out.”

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Capital One·Data Scientist·Technical Phone Screen

Jul 2026

Case-style interview for a Data Scientist role at Capital One built around an energy company transitioning off fossil fuels. Heavy on back-of-envelope math and strategic reasoning, with a few curveball follow-ups that pushed beyond the numbers.

What factors would you consider when evaluating a company's transition from fossil fuels to renewable energy?
Given a fossil-fuel plant with 8.8 million MWh annual capacity, a $5M monthly lease, $25M yearly fixed cost, $20/MWh variable cost, $40/MWh revenue, and a $400M initial investment, how many MWh must be produced annually to recover 10% of that initial investment?
Does the production volume you calculated actually make sense given the plant's maximum capacity?
If government policy caps fossil-fuel output at 5 million MWh per year, which alternative energy sources should the company pursue and why?
If no new energy sources are added despite the government cap, what levers could the company pull to maintain profitability?
A solar test plant costs $12.5M upfront. It produces 150k MWh when sunny (75% of the time) and 50k MWh when cloudy (25% of the time), with zero variable cost and $40/MWh revenue. How many years to break even?
An ethanol test plant costs $2.5M upfront, produces 100k MWh per year, has a $30/MWh variable cost, and sells at $40/MWh. How many years to break even?
With no budget constraint, which test plant would you recommend and why?

“Felt pretty open-ended so I just started listing things: capex, regulatory risk, grid reliability, public sentiment.”

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Capital One·Data Scientist·Technical Phone Screen

Jul 2026

Capital One data scientist tech round where they handed me three imputation class implementations and asked me to tear them apart. Code review style, which I wasn't fully expecting going in.

Given three imputation class implementations covering mean, median, and mode substitution, what problems or risks do you see in the code?
How would you refactor these imputation classes to be more robust and reusable, and what design patterns or interface conventions would you apply?

“I started picking at surface stuff like missing null checks and then kind of stalled.”

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Capital One·Software Engineer·Technical Phone Screen

Jul 2026

Capital One software engineer interview that was basically one meaty class design question about a banking account service. Not a lot of fluff, they just dropped the problem and let you run with it.

Design and implement an AccountService class that supports deposit, withdraw, transfer, and getBalance operations, with proper handling for insufficient funds, atomicity on transfers, and thread safety.

“The basic CRUD part was fine, I had that sketched out in a few minutes.”

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Capital One·Data Scientist·Technical Phone Screen

Jul 2026

Capital One data scientist interview with a credit card product case. The core question was a break-even analysis requiring you to work through the revenue and cost structure of a cashback card versus a no-cashback card. Pretty quantitative for a DS role but not surprising given the domain.

Walk through the main revenue and cost components for a credit card issuer. Then, given that both a cashback and a no-cashback card charge the same interest rate on balances and earn the same interchange rate on transactions, and that no-cashback users carry an average balance of $1,000, what average balance would cashback cardholders need to carry for the cashback product to break even?

“I started listing revenue sources fine (interchange, interest income) but fumbled on the cost side.”

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Capital One·Software Engineer·Online Assessment (OA)

Jul 2026

Capital One SWE interview with a grid simulation problem. Not the hardest thing I've ever seen but there are enough edge cases to trip you up if you're not careful about placement order and overlap logic.

Given integers n and m and an ordered list of figures (each being one of five predefined shapes), construct an n x m grid initialized to zero. For each figure in order, find the first valid top-left placement position in row-major order where the shape fits within bounds and doesn't overlap any already-placed cells. Fill those cells with the figure's 1-based index. If no valid placement exists, skip it. Return the final grid.

“The shape definitions are handed to you so that part isn't the puzzle.”

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Capital One·Data Scientist·Onsite - Product Sense / Strategy

Jul 2026

Capital One data scientist interview with a meaty product strategy case. The kind of question that sounds like it belongs in a consulting interview, not a DS loop, so I wasn't totally prepared for the scope of it.

Should the company invest in R&D to develop a vegan burger right now? Build a full business case including market sizing, expected margins, break-even timeline, key risks, and option value from future product extensions. Then propose a staged pilot plan with success and kill criteria.

“Way more layers than I expected.”

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Capital One·Data Scientist·Technical Phone Screen

Jul 2026

Capital One data scientist interview with a pretty involved operations/pricing case. Two parts to the same problem, and the second part is where things get interesting. Not a typical SQL or ML question at all.

A ride-share service runs 2,400 rides per day at $30 each. Drivers cost $700/day, work 8-hour days, and can do at most 5 rides per hour. Fixed costs are $10,000/day and you have to hire drivers for full days. How many drivers do you need to meet demand, and what is the daily profit? Show your work and confirm capacity actually covers demand.
Now split the day into two 4-hour blocks. Non-peak has 800 rides at $30 each, peak has 1,600 rides at some price P. Driver constraints and costs are the same, drivers still hired for the full day. What price P makes daily profit exactly zero? State any assumptions if capacity becomes a binding constraint.

“This part I actually got through cleanly.”

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