The Quant Brief

Quant Careers · Markets · Recruiting

Optiver Is Hiring 158 Quants. They're Not All PhDs Anymore.

Inside the 2026 quant hiring wave - and why working engineers and master's students are landing the seats that used to go straight to physics PhDs.

If you've watched the prop trading job market over the last 18 months, you've probably noticed something quietly remarkable: the firms that used to recruit almost exclusively from a half-dozen elite PhD programs are running their widest hiring funnel in a decade.

Optiver currently lists 158 open quant and quant-adjacent roles in its New York, Chicago, and Austin offices. The firm's own posted compensation floor for entry-level quant trader and quant researcher roles in NYC: $200,000 base, with most first-year total compensation landing between $300,000 and $475,000 once bonus and sign-on hit.

And Optiver is not the outlier. It's the rule.

Across a dozen tier-1 proprietary trading firms tracked by recruiters this cycle - Jane Street, Citadel, Citadel Securities, Two Sigma, Hudson River Trading, DRW, Jump, IMC, Five Rings, SIG, Akuna, and Optiver - the aggregate count of open quant roles for 2026 hiring sits above 1,400.

That is a generational hiring wave. And it is happening with almost no broad-market press coverage.

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What's driving the surge

Three things, mostly.

First, market making has become enormously profitable in the post-2022 volatility regime. When realized volatility runs hot, bid-ask spreads earn more per round-trip, and high-frequency market makers print money. Firms reinvest by hiring.

Second, an entire generation of senior traders - the cohort that joined when prop trading was still a niche, pre-2010 - is now in the early-retirement window. Replacement hiring has compounded.

Third, the firms are racing each other for the same engineers, mathematicians, and physicists. When Citadel raises starting comp, Jane Street responds. When Jane Street offers a $200K sign-on, Optiver matches. The result is a comp escalator that has roughly doubled entry-level offers since 2019.

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The shift in who's getting hired

Here is the part recruiters are most reluctant to say out loud, because it cuts against the field's own mythology:

The "you need a Princeton PhD" filter is functionally dead at most tier-1 prop firms.

We pulled background data from publicly available 2024 and 2025 quant hires across six firms. Of new entry-level quant traders and junior quant researchers:

• 41% held only a bachelor's degree at time of hire
• 34% had a master's degree (most commonly in financial engineering, statistics, computer science, or applied math)
• 25% held a PhD

Of the bachelor's-and-master's cohort, a striking number came from non-traditional pipelines: working software engineers transitioning out of tech, math and statistics graduates with one or two years in adjacent quantitative roles, competitive programmers, and poker professionals.

What the firms are actually screening for is not credentials. It is what one Jane Street recruiter called, on background, "quantitative intuition under pressure." That is - can you think probabilistically when the clock is running, can you compute expected values in your head fast enough to defend a market, and can you code well enough in Python to prototype an idea before lunch.

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What the interviews actually look like

The opacity of quant hiring is part of why so many capable candidates wash out. Most don't fail because they're not smart enough. They fail because they walked in not knowing what was being tested.

Across Optiver, Jane Street, Citadel, and Hudson River, the first-round screen is functionally identical:

1. Mental math under time pressure. Candidates are asked to multiply two-digit numbers, compute percentages, and convert between fractions and decimals - in their head, in roughly 8 seconds per problem. Optiver's "80 in 8" test (80 questions in 8 minutes) is the most famous version. Jane Street uses a less public but functionally similar drill.

2. Probability and expected value problems. Coin flips. Dice. Card draws. The questions sound elementary. They are not. The expected-value math is straightforward; the trap is that most candidates have never trained to do it fast and to defend the answer when the interviewer pushes back.

3. Market making intuition. A small number of firms - Optiver and IMC most notably - run a live "make me a market" exercise in round 2 or 3. You're given a quantity to price. You quote a two-sided market. The interviewer trades against you. You update. This is the round most candidates have no preparation for at all. It is also the round that separates offers from rejections.

4. A Python coding screen. Usually a single hour-long take-home or live problem. Not a leetcode grind. More commonly: write a clean simulation of a probability scenario, or implement a small data-processing task. Firms want to see you can think in code, not memorize patterns.

None of this requires a PhD. All of it requires preparation that most applicants never receive.

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The training gap

There is no undergraduate course in the United States that teaches the actual quant interview. There are textbooks - Heard on the Street, A Practical Guide to Quantitative Finance Interviews, Quant Job Interview Questions and Answers - and they are all useful as reference. None of them simulate the pressure, the speed, or the live "make me a market" exercise.

This is the training gap. And it is the reason most candidates - even strong candidates from top engineering and quantitative programs - fail their first three to five interviews before they ever get an offer.

The 2024 Optiver intern survey, conducted internally and shared with us on background, put the figure at roughly 92% of first-round interviewees do not advance. Of those who do advance, more than half do not receive an offer.

So when you see the headline "158 open roles at Optiver," understand what that funnel looks like in practice. The firm will screen well over 6,000 candidates to fill those seats. The difference between being in the 6,000 and being in the 158 is not raw intelligence. It is targeted, deliberate preparation against an interview process most applicants don't know how to study for.

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How serious candidates are preparing in 2026

The candidates landing tier-1 seats this cycle are doing three things differently.

They are training mental math daily, not in cram sessions. 15 minutes a day for 6-8 weeks is more effective than 4 hours on a Saturday.

They are working through probability and expected value problem sets with a clock - not just for accuracy, but for speed and for defense. Being right in 20 seconds is not the same as being right in 4 seconds and being able to explain it.

They are practicing live market making against a partner before they get to interview round. There is no substitute for the muscle memory of quoting a market while someone disagrees with your price.

And they are writing Python every week, not memorizing leetcode patterns. The firms want to see how you think in code, not whether you can recall a sorting algorithm.

This is the preparation framework Wall Street Quants has built into its program for working professionals and graduate students pursuing tier-1 prop firm roles. The team is running a free, live information session next week walking through the framework, the firms currently hiring, and the specific skills tested in 2026 interviews.

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Who this session is for

The team has been candid about who they built this for - and who they didn't.

This session is for:

• Working engineers, math and statistics graduates, current quants, and master's students pursuing entry-level or lateral roles at firms like Optiver, Jane Street, Citadel, Hudson River, DRW, and Two Sigma
• Candidates comfortable with the idea of training Python, probability, mental math, and market making for 8-12 hours per week
• Career switchers serious about $200K+ entry-level compensation

It is not for:

• Casual finance hobbyists
• Portfolio traders looking to optimize personal trading strategies (Wall Street Quants offers a separate program for this audience)
• Anyone unwilling to commit to structured preparation

If you fit the first list, the session will save you months of trial and error. If you fit the second, it will not be a productive use of your time.