Quantitative Developer, Trading Team

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 seeking a Quantitative Developer to design, build and maintain our systematic trading platform. You will partner closely with traders, researchers and infrastructure engineers to turn trading ideas into production-grade strategies executing across global markets.

• Design, develop and maintain high-performance trading systems covering market connectivity, order management and execution strategies.
• Collaborate with quantitative traders to transform research strategies into robust, production-ready code.
• Build and optimize data pipelines, back-testing frameworks and simulation environments.

• 3-5 years' experience developing and optimizing quantitative trading systems, including: – Exchange/market-data APIs – Real-time strategy and portfolio logic – Order-routing, risk and position management
• 1+ year of hands-on Rust experience in production environments.
• Strong programming skills in Rust and Python; experience with C++ is a plus.
• Solid experience with databases and SQL; exposure to KDB/q is a strong plus.
• Bachelor s or higher degree in Computer Science, Software Engineering or a related technical field.
• Experience applying machine-learning frameworks (PyTorch, Tensor Flow, scikit-learn) to trading problems is a plus.

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