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Optiver·Software Engineer·Online Assessment (OA)·Intermediate

Intermediate
May 2026

Summary

Optiver-style online quant assessment for a software engineering role. Rapid-fire probability and logic questions under serious time pressure, no calculator allowed. Some of it is straightforward mental math, but a couple questions are designed to trip you up if you overthink them.

Questions Asked (5)

Q1

You roll a fair six-sided die twice. What is the probability the second roll shows a different value than the first?

Algorithms & Data Structures
Author's notes

Pretty easy warmup.

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AI HintsAI Generated

Suggested Approach

Use the complement rule: calculate the probability that the second roll is the same as the first, then subtract from 1. Alternatively, condition on the first roll and count favorable outcomes for the second roll.

Pro tip: State your assumptions clearly (fair die, independent rolls) and consider mentioning both the complement and direct counting methods to show versatility. For trading firms like Optiver, emphasize quick mental math and logical reasoning.

1. Understand the problem

Clarify that we roll a fair six-sided die twice, and we want the probability that the second roll differs from the first. Assume independence and fairness.

2. Choose a method

Decide between using the complement rule (1 - P(same)) or direct counting (condition on first roll). Both are valid; pick the one you find quicker.

3. Compute probability of same

If using complement: The probability the second roll equals the first is 1/6, since there is exactly one matching outcome out of six equally likely outcomes.

4. Compute probability of different

Subtract from 1: 1 - 1/6 = 5/6. If using direct counting: After any first roll, 5 of the 6 possible second rolls are different, so probability is 5/6.

5. Verify and present

Check that the answer makes sense (e.g., probability should be high since only one match is possible). Present the answer clearly, stating the final probability as 5/6 or approximately 83.33%.

Key Points to Mention

  • Independence of die rolls
  • Fair six-sided die (each outcome equally likely)
  • Complement rule: P(different) = 1 - P(same)
  • Conditional probability: given first roll, second roll has 5 favorable outcomes out of 6
  • Final answer: 5/6 or about 83.33%
  • Alternative method: direct counting of outcomes (30 favorable out of 36 total)

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.

Q2

You take a shuffled 52-card deck and discard the top 10 cards face-down without looking at them. What is the probability the 11th card is red?

Algorithms & Data Structures
Author's notes

This one is sneaky if you're not careful.

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AI HintsAI Generated

Suggested Approach

Recognize that discarding cards face-down without looking does not change the probability for any remaining card. The 11th card is equally likely to be any of the 52 cards, so the probability it is red is simply the proportion of red cards in the deck. State the answer clearly and explain the symmetry argument.

Pro tip: Emphasize that the discarding process is irrelevant because the cards are not observed; this demonstrates understanding of conditional probability and symmetry. Avoid overcomplicating with conditional cases unless asked to elaborate.

1. Understand the problem

Identify that we have a standard 52-card deck with 26 red and 26 black cards. We discard 10 cards face-down without looking, then ask for the probability that the 11th card is red.

2. Recognize symmetry

Since the discarded cards are not observed, the remaining deck is still a random permutation of all 52 cards. Thus, the 11th card is equally likely to be any of the 52 cards.

3. Compute probability

The probability that a randomly chosen card is red is the number of red cards divided by total cards: 26/52 = 1/2.

4. State the answer

Clearly state that the probability is 1/2 or 50%, and briefly explain why the discarding step does not affect the result.

Key Points to Mention

  • Standard deck composition: 26 red, 26 black.
  • Discarding cards face-down without looking provides no information about their colors.
  • The 11th card is equally likely to be any of the 52 cards due to symmetry.
  • Probability = number of red cards / total cards = 26/52 = 1/2.
  • The result is independent of the number of cards discarded, as long as they are not observed.
  • This is a classic example of conditional probability where conditioning on unobserved events does not change the probability.

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.

Q3

You roll two fair dice. What is the probability the sum equals 11 or 12?

Algorithms & Data Structures
Author's notes

36 total outcomes.

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AI HintsAI Generated

Suggested Approach

Clarify that the dice are fair and independent, then compute the total number of equally likely outcomes (36). Count the favorable outcomes for sum 11 (2 ways) and sum 12 (1 way), add them, and divide by 36 to get the probability.

Pro tip: State the answer as a simplified fraction (1/12) and mention that the events are mutually exclusive, so you add probabilities. This shows you understand both the calculation and the underlying probability rules.

1. Define the sample space

Each die has 6 faces, so there are 6 × 6 = 36 equally likely outcomes when rolling two fair dice.

2. Identify favorable outcomes for sum 11

List the pairs that sum to 11: (5,6) and (6,5). That gives 2 favorable outcomes.

3. Identify favorable outcomes for sum 12

List the pairs that sum to 12: (6,6). That gives 1 favorable outcome.

4. Combine favorable outcomes

Since the events are mutually exclusive, add the counts: 2 + 1 = 3 favorable outcomes.

5. Compute and simplify the probability

Divide favorable outcomes by total outcomes: 3/36 = 1/12. State the final answer clearly.

Key Points to Mention

  • Fair dice: each outcome is equally likely.
  • Total number of outcomes: 36.
  • Sum 11 can occur in 2 ways: (5,6) and (6,5).
  • Sum 12 can occur in 1 way: (6,6).
  • Events are mutually exclusive, so add probabilities: P(11) + P(12) = 2/36 + 1/36 = 3/36.
  • Simplify fraction to 1/12.

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.

Q4

You flip a fair coin 3 times. What is the probability all three flips show the same result?

Algorithms & Data Structures
Author's notes

Two favorable sequences out of 8 total: HHH and TTT.

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AI HintsAI Generated

Suggested Approach

Clarify that the coin is fair and flips are independent, then compute the probability of all heads and all tails separately, and sum them. Alternatively, count the favorable outcomes (HHH, TTT) out of 8 equally likely outcomes. State the final probability as 1/4.

Pro tip: Show that you can generalize: for n flips, the probability is 2*(1/2)^n = (1/2)^(n-1). This demonstrates pattern recognition and mathematical maturity, which is valued in quantitative roles.

1. Clarify assumptions

Confirm that the coin is fair (probability 1/2 for heads or tails) and that flips are independent. This ensures a common understanding before calculating.

2. Identify the sample space

List all possible outcomes of 3 flips: there are 2^3 = 8 equally likely sequences (HHH, HHT, HTH, HTT, THH, THT, TTH, TTT).

3. Count favorable outcomes

Determine which outcomes satisfy 'all three flips show the same result': HHH and TTT. So there are 2 favorable outcomes.

4. Compute probability

Divide the number of favorable outcomes by the total number of outcomes: 2/8 = 1/4. Alternatively, compute P(all heads) + P(all tails) = (1/2)^3 + (1/2)^3 = 1/8 + 1/8 = 1/4.

5. State the answer clearly

Conclude that the probability is 1/4 or 25%. Optionally, mention the general formula for n flips: 2*(1/2)^n = (1/2)^(n-1).

Key Points to Mention

  • Independence of coin flips
  • Fair coin means each outcome has probability 1/2
  • Total number of outcomes for 3 flips is 2^3 = 8
  • Favorable outcomes are HHH and TTT
  • Probability = favorable outcomes / total outcomes = 2/8 = 1/4
  • Generalization: for n flips, probability = (1/2)^(n-1)

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.

Q5

61 coins are randomly distributed into 15 boxes. What is the probability that at least one box contains more than 4 coins?

Algorithms & Data Structures
Author's notes

I spent a moment trying to set up a combinatorics calculation before realizing this is just pigeonhole.

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AI HintsAI Generated

Suggested Approach

Use complementary counting: calculate the probability that no box has more than 4 coins, then subtract from 1. The total number of ways to distribute 61 identical coins into 15 distinct boxes is C(75,14). The favorable ways are the number of solutions to x1+...+x15=61 with each xi ≤ 4, which can be found using inclusion-exclusion or generating functions.

Pro tip: In probability problems with 'at least one', always consider the complement first. Also, clarify whether coins are identical or distinct; for this question, identical coins lead to a cleaner combinatorial solution.

1. Identify the complement event

The event 'at least one box has more than 4 coins' is easier to handle via its complement: 'no box has more than 4 coins' (i.e., each box has at most 4 coins).

2. Compute total number of distributions

Assuming identical coins and distinct boxes, the total number of ways to distribute 61 coins into 15 boxes is the number of nonnegative integer solutions to x1+...+x15=61, which is C(61+15-1,15-1)=C(75,14).

3. Count favorable distributions for the complement

Count the number of solutions to x1+...+x15=61 with 0 ≤ xi ≤ 4 for all i. This can be done using inclusion-exclusion or generating functions: coefficient of x^61 in (1+x+...+x^4)^15.

4. Compute the complement probability

Divide the favorable count by the total count to get P(no box >4). Then the desired probability is 1 minus this value.

5. Simplify and present the final answer

If possible, simplify the expression or provide a numerical approximation. State the final probability clearly.

Key Points to Mention

  • Complementary counting: P(at least one >4) = 1 - P(all ≤4).
  • Stars and bars formula for total distributions: C(75,14).
  • Inclusion-exclusion principle to enforce upper bounds: subtract cases where one or more boxes have ≥5 coins.
  • Generating functions: coefficient of x^61 in (1+x+...+x^4)^15.
  • Assumption of identical coins; if coins are distinct, the problem changes to multinomial coefficients.
  • Numerical computation may be required; be prepared to discuss how to calculate large binomial coefficients.

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.