DRW Quantitative Trader Interview Guide

The short answer: DRW publishes four steps for its trading graduates and interns: an online application, a timed technical challenge on probability and logic, a phone or Zoom interview of about 45 minutes, and a final round over two days at a DRW office. For Quantitative Trading Analyst candidates, DRW says the final includes a quantitative coding challenge in Python, a trading simulation and several technical interviews. Candidate reports describe the challenge as about 6 questions in 45 minutes on probability, expected value, Markov chains and brain teasers. DRW says the process may vary by team, so treat this as the usual quant trader path. Last reviewed October 2026.

DRW quantitative trader interview: quick answers

The DRW quantitative trader role

What DRW quantitative traders work on, the skills its job postings ask for, and what a week can look like. DRW posts the role as Quantitative Trading Analyst and Quantitative Trading Analyst Intern (campus); Floor Trader (new grad, Chicago); Trader, Quantitative Trader - Futures and US Equity Index Options Trader (experienced).

DRW quantitative trader levels and pay

Your level sets the bar you are interviewed against and the pay band of the offer.

DRW does not publish a level ladder. The rows below are the trader titles in its postings, from the internship up to a senior futures role that asks for 7 or more years.

Pay in DRW's US job postings

DRW's Chicago trader postings state a base salary or range and say each role is eligible for an annual discretionary bonus.

The intern figure is stated as an annual base for a 10-week internship, so an intern earns a pro-rated share of it; housing is provided. No US new-grad Quantitative Trading Analyst posting was open (the open one is in London), so there is no QTA row. Ranges seen October 29, 2026.

DRW quantitative trader interview process

The stages follow DRW's graduate and intern pages and its own articles on the technical challenge, the phone interview and the final round. Question counts and topics inside the challenge come from candidate reports.

Based on DRW's own pages and candidate reports.

DRW does not publish a decision timeline or a reapplication policy. One intern candidate reported an offer about 10 days after the final round, a single data point. Last reviewed October 2026.

What is different at DRW

• The campus trader title is Quantitative Trading Analyst (QTA). A QTA tests a trader's idea through data analysis, model building and back testing, then works with engineers and researchers so the trader can execute it. DRW also uses QTA above new-grad level (a London posting asks for 1 to 2 years). Trader, Quantitative Trader - Futures and US Equity Index Options Trader are experienced seats, and US Trading Analyst in Houston is a trade operations role, not a trading seat.
• Python matters more than at many trading firms. The QTA final includes a quantitative coding challenge in Python next to the trading simulation, and DRW's own prep advice names pandas, numpy and scipy.
• The final round is a two-day visit to a DRW office, with a technical challenge on the first afternoon before a full day of interviews.
• DRW also hires new grads as Floor Traders in Chicago. They join a training program and split time between the Cboe trading floor and DRW's desk, a floor and voice trading path next to the more systematic QTA track. Prior trading experience is not required.
• DRW trades its own capital across fixed income, ETFs, equities, FX, commodities and energy, and also runs real estate, venture capital and crypto businesses. Desks named in postings include US index and equity options and delta-one futures in the FICCO options business.
• DRW does not publish a rule on AI use in interviews; ask your recruiter.

DRW quantitative trader interview questions

Questions from our bank, then practice prompts we wrote for this guide around DRW's work.

1from typing import List, Tuple
2
3def backtest(prices: List[float], window: int, band: float) -> Tuple[float, float]:
4    """Return (total_pnl, max_drawdown) for the mean-reversion rule, rounded to 2 decimals."""
5    pass

1from typing import List, Tuple
2
3def backtest(prices: List[float], window: int, band: float) -> Tuple[float, float]:
4    pnl = peak = drawdown = 0.0
5    running = 0.0
6    for t in range(len(prices) - 1):
7        running += prices[t]
8        if t >= window:
9            running -= prices[t - window]
10        position = 0
11        if t >= window - 1:
12            avg = running / window
13            if prices[t] < avg - band:
14                position = 1
15            elif prices[t] > avg + band:
16                position = -1
17        pnl += position * (prices[t + 1] - prices[t])
18        peak = max(peak, pnl)
19        drawdown = max(drawdown, peak - pnl)
20    return round(pnl, 2), round(drawdown, 2)
21
22# A running sum keeps each average O(1).
23# Complexity: O(n) time, O(1) extra space.

How to prepare

A plan for the DRW loop, most important first:

1. Prepare for the timed challenge: probability, expected value, Markov chains and brain teasers under a clock, with answers rounded as stated.
2. Get comfortable writing Python with pandas and numpy on a small data task, since the QTA final includes a Python coding challenge.
3. Practice taking risk in games: betting, poker-style games or paper trading, as DRW suggests, to prepare for the trading simulation.
4. Review mental math and statistics for the 45-minute phone interview, and rehearse explaining every project on your resume.
5. Learn options basics (delta, gamma, hedging) and follow the markets, since DRW asks quant trading candidates about recent events.
6. Prepare stories that show curiosity and a proactive attitude, the qualities DRW names for QTAs.

Practice path

Courses that cover the rounds above:

• Probability for Quant Interviews
• Estimation for Trading Interviews
• Financial Mathematics