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Quant Researcher Track

Pass the research panel at
the systematic giants.

Statistics, time series, signal construction, and the Python data-handling problems Two Sigma, D.E. Shaw, Citadel, and Point72 actually ask. Prep that pairs theory drills with the applied questions you face on the desk.

Research roles tracked at

What this track actually tests

The four corners of the round

Each capability below is a real round you'll sit. Surface them up front so prep aims at the right thing, not generic interview practice.

01 · Probability

Bayes, expectation, and the long-tail traps

Conditional expectation, optional stopping, martingales, and the deceptively simple bets that hide a Borel paradox. The first-round filter at Two Sigma and D.E. Shaw.

02 · Time series

Stationarity, regimes, and signal noise

AR/MA, cointegration, regime-switching, and the practical questions of separating real signal from leakage. The applied stats that the research panel actually leans on.

03 · Python

Vectorised pandas, no for-loops in sight

Realistic research problems framed in pandas/NumPy. Backtest a signal, decompose a return stream, debug a leaky cross-validation. The kind of one-shot script you'd write on a desk.

04 · ML

Where the model breaks before it ships

Cross-validation pitfalls, leakage, regularisation, and the 'why did this work in backtest but not live' diagnostic that distinguishes a researcher from someone who runs scikit-learn.

Topics on this track

Drill what interviewers actually ask

Each topic is a tagged subset of the question pool. Click through to practice every question in that category.

Practice by firm

Train on the firm you're targeting

Every question is tagged with the firms that ask it. Filter to the firm whose interview is on your calendar.

Comp snapshot · 2026

What this track actually pays

Bands sourced from the Myntbit /comp dataset. Numbers are the most recent confirmed across 8 firms hiring this track.

Intern
$10k–$14k/mo
New grad
$190k–$370k
Senior
$500k–$1.2M

Researcher comp is bonus-heavy and PnL-tied. Senior bands stretch wide; a top performer at Two Sigma or Citadel can multi-x the median in a strong year.

See full comp dataset

Need fundamentals first?

Bridge to /learn before you drill

Lessons covering the math, coding, and markets fundamentals that this track's questions assume. Skip to practice when you're ready.

Frequently asked

Researcher track questions

Do I need a PhD to interview as a quant researcher?
No, but PhD + strong research portfolio is the baseline path for Two Sigma, D.E. Shaw, and Renaissance. Citadel, Point72 (Cubist), and Millennium hire master's-level researchers more readily, especially with applied ML or finance research experience.
What's the difference between a researcher and a trader role?
Researcher = build the signal. Trader = trade against it. Research panels test math, stats, and ML; trader rounds test market intuition and pricing speed. The same firm often has both; the track is the same firm but a different desk.
How important is the math relative to the coding?
At Two Sigma and D.E. Shaw, math/stats slightly edges coding. At Citadel and Point72, the balance flips toward applied: you'll be expected to ship a working notebook against a research prompt, not just whiteboard a derivation.
Where does the compensation data come from?
From the /comp dataset: crowdsourced base + bonus + equity submissions from people on the desk plus verified hires. Researcher bands are bonus-heavy because PnL allocations dominate the picture.

Start drilling the researcher track

2,134+ questions · 8 firms · 2 curated plans · free to start

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