Optiver Interview Questions — Page 1

Optiver·Software Engineer·Technical Phone Screen

Apr 2026

Quant Engineer interview at Optiver with a probability/stochastic processes question that sounds deceptively simple but has a non-obvious answer if you haven't seen it before.

Consider a 2D random walk where a particle moves up, down, left, or right each with equal probability. What is the probability that the particle eventually returns to the origin?

“The answer is 1, it returns with certainty, same as 1D.”

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Optiver·Software Engineer·Onsite - Behavioral / Leadership

Apr 2026

Behavioral round at Optiver for a software engineering role. One question, fairly open-ended, the kind that sounds easy until you're actually sitting there trying to pick three traits that don't make you sound like a LinkedIn profile.

How would your peers, manager, and cross-functional partners describe you? Pick three traits and support each with a specific example.

“I fumbled the structure on this.”

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Optiver·Software Engineer·Technical Phone Screen

Apr 2026

Optiver quant engineer interview with a sequence puzzle that looks deceptively simple until you actually try to find the recurrence. No outcome info shared, but the problem itself is worth knowing about.

Find the missing term in the sequence 2, 1, 2, 5, 13, 73/2, ? and explain the rule governing it.

“I stared at this way too long looking for an arithmetic or geometric pattern before accepting it was something nonlinear.”

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Optiver·Data Scientist·Onsite - System Design / Architecture

Apr 2026

Optiver Data Scientist interview with a system design question that felt more like a low-latency engineering problem than anything I'd associate with a DS role. Threw me off a bit but also kind of interesting once I got into it.

You're given a 7-8 character alphanumeric reference code and four candidate codes. Design a system that finds the exact match as fast as possible, handles streaming batches at increasing rates with low latency, and optionally tolerates OCR-style input errors via a configurable similarity threshold. Walk through your data structures, algorithmic choices, complexity, and how you'd benchmark and scale it.

“This one took me a second to parse because it sounds deceptively simple.”

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Optiver·Software Engineer·Online Assessment (OA)

Apr 2026

Optiver's online assessment for the software engineer role is basically a probability and stats gauntlet. 30 questions, brutal time limits, the kind of thing where your mental math either holds up or it doesn't.

You have 30 probability and statistics questions with strict time limits. How do you manage your time, decide which problems to tackle first, and verify your answers under pressure? Which techniques do you lean on most?

“The time pressure is the actual test, not the math.”

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Optiver·Software Engineer·Technical Phone Screen

Apr 2026

Optiver software engineer interview that leaned hard into CS fundamentals. The data structures question was basically a full oral exam on its own, covering everything from arrays to graphs with complexity analysis and real-world tradeoffs.

Walk through the common data structures (arrays, linked lists, stacks, queues, hash tables, BSTs, heaps, graphs) and for each one: give average and worst-case time and space complexities for search, insert, delete, and iteration; describe the key invariants; and give an example where it shines and one where it falls apart.

“This question is a monster.”

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Optiver·Software Engineer·Onsite - System Design / Architecture

Apr 2026

Optiver system design round that went way deeper than I expected. Started with 'design the network for a trading firm' and two hours later I was explaining where individual microseconds disappear in the order-flow path. Brutal but genuinely interesting if you're into low-latency infrastructure.

Design the full network and infrastructure for a trading firm that has servers co-located next to an exchange and traders working from a remote office. Walk through physical wiring choices, bandwidth and latency requirements, server hardware and OS tuning, kernel-bypass networking, time synchronization, redundancy and failover, and the complete order-flow path end-to-end.
For TCP/IP specifics: explain Nagle's algorithm, how congestion control behaves in a low-latency trading context, when retransmits become a problem, and where you would choose UDP over TCP.
Walk through the complete order-flow path from a trader clicking 'send' at the remote office to the order hitting the exchange matching engine. Account for where each microsecond is spent.

“This was the whole interview basically.”

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Optiver·Data Scientist·Onsite - Multi Round

Apr 2026

Optiver data scientist interview included a market-making game where you quote intervals on estimation questions and get scored on tightness vs coverage. Five rounds, need a cumulative 2.0 to pass. Genuinely one of the more interesting interview formats I've seen, but the math sneaks up on you fast.

You're playing a 5-round market-making game where each round you quote a closed interval [L, U] around an unknown positive quantity. If the true answer falls inside your interval you score L/U, otherwise zero. Your total across all five rounds needs to reach 2.0 to pass. How do you analyze and play this game?
For a single round of the game, how do you choose the optimal interval [L, U] given your subjective uncertainty about the true answer?
If you use a fixed ratio r = U/L every round, how does your pass probability depend on r? Compare a few different tightness levels.
How should you adapt your interval tightness across rounds if you can observe your running score after each round?
What if one of the estimation questions has uncertainty spanning several orders of magnitude? What does the scoring rule imply about your attainable score in that round?
If you could see all five questions before quoting any intervals, how would you allocate risk across them differently than if you had to answer sequentially?

“This was the whole interview basically.”

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Optiver·Software Engineer·Technical Phone Screen

Apr 2026

Quant Engineer round at Optiver with a pretty gnarly probability/statistics question dressed up as a sports analytics problem. No fluff, just math and reasoning under pressure.

You're given a full round-robin results table for five soccer teams. For an upcoming match between two of them, rank three events by probability: one team wins, the match draws, or total goals exceed 2.5. Justify your ordering using the empirical data from the table.

“This one wrecked me a little.”

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Optiver·Software Engineer·Technical Phone Screen

Apr 2026

Optiver SWE interview with a pretty involved algorithmic problem called OptiCargo. Two parts: a batch optimization problem and a streaming version of the same thing. The problem itself was interesting but there's a lot going on and I felt like I was constantly behind.

Given a set of flights (each with a cost, capacity, and arrival time) and a set of cargo jobs (each with a weight, revenue, and deadline), design an algorithm to select which flights to book and which cargo to assign to each flight in order to maximize total profit.
Extend your solution to work as a streaming class: flights and cargo arrive as events over time, and the system should maintain a current best plan that can be queried at any point.
How would your system handle the case where a flight booking attempt fails after you've already planned to use it?

“This is basically a variant of a knapsack problem but with two layers: you're picking flights AND packing cargo into them, and the flight cost only hits you if you actually book it.”

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