Quantitative Trading Analyst

DRW is a diversified trading firm with over 3 decades of experience bringing sophisticated technology and exceptional people together to operate in markets around the world.

We value autonomy and the ability to quickly pivot to capture opportunities, so we operate using our own capital and trading at our own risk.

Headquartered in Chicago with offices throughout the U.S., Canada, Europe, and Asia, we trade a variety of asset classes including Fixed Income, ETFs, Equities, FX, Commodities and Energy across all major global markets.

We have also leveraged our expertise and technology to expand into three non-traditional strategies: real estate, venture capital and cryptoassets.

We operate with respect, curiosity and open minds.

The people who thrive here share our belief that it’s not just what we do that matters–it's how we do it.

DRW is a place of high expectations, integrity, innovation and a willingness to challenge consensus.

We are looking for a Quantitative Trading Analyst (QTA) to join a volatility-focused trading team.

This role is ideal for candidates with 1–2 years of experience in trading, quantitative research, market making, or systematic strategies who are interested in applying quantitative thinking to volatility markets.

Prior experience across a variety of asset classes is welcome — including equities, rates, credit and FX.

What you’ll do

• Analyze, improve and implement trading strategies
• Develop and maintain quantitative models, analytics, and trading tools
• Analyze large datasets to identify market opportunities, inefficiencies, and risk exposures
• Actively manage live market trading algorithms
• Provide liquidity in options via systematic algos and voice in IDB markets
• Conduct research into volatility dynamics, pricing, and market microstructure
• Collaborate with technology teams to improve trading infrastructure and automation
• Support new product and market expansion initiatives across asset classes

What we’re looking for

• 1–2 years of experience in trading, quantitative analysis, research, or a related role
• Strong academic background in mathematics, physics, computer science, engineering, or a similarly quantitative discipline