Quantitative Researcher

Our formula for success is to hire exceptional people, encourage their ideas and reward their results.

As a Quantitative Researcher, you will develop mathematical models using advanced statistical learning methods to build automated trading strategies across multiple asset classes. Our research team collaborates on idea generation and strategy development, while encouraging independent exploration and original approaches. You will have access to clean data integrated with compute resources and the support of experienced researchers, traders and dedicated software developers. You will conduct quantitative analysis of market data to uncover relationships and identify historical trends. We do not require familiarity with or prior experience in financial markets for this role. We will give you the training you need to be successful.

How you will make an impact

• Extract predictive signals from financial data through both traditional statistical analysis methods and cutting edge machine learning techniques
• Assist software developers to translate research strategies into production software
• Optimize the order execution and risk management of our trading system
• Create robust solutions to problems presented in the trading environment
• Formulate and apply mathematical modeling techniques to enhance existing trading strategies and perform innovative new research with the goal of identifying and capturing trading opportunities
• Automate human-decision based trading strategies; prototype algorithmic trades from trading ideas

You will be right at home if you have…

• A degree in a technical discipline with a focus on statistics, machine learning, signal processing, optimization and control graduating between December 2025 and September 2026 (Bachelor’s, Master’s, PhD)
• A curiosity for model development and experience handling large data sets
• Expertise in programming using Python, R, MATLAB, or C++ for conducting research
• Can advocate for your beliefs in a concise and effective way with the team
• Significant hands-on experience applying machine learning algorithms to real world problems
• Strong problem-solving and statistics skills
• The proactive ability to take the lead on assignments and deliver practical research results in a timely manner

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’snot 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.

For more information about DRW's processing activities and our use of job applicants' data, please view our Privacy Notice at https://drw.com/privacy-notice .

Accepted file types: pdf, doc, docx, txt, rtf

Enter manually

Accepted file types: pdf, doc, docx, txt, rtf

Education

School * Select...

Degree * Select...

Select...

Select...

Start date year *

End date month * Select...

End date year *

Legal First Name (if different from preferred name)

Legal Last Name (if different from preferred name)

LinkedIn Profile

Website

Please provide a copy of your most recent transcript from your highest degree level. *

Accepted file types: pdf, doc, docx, txt, rtf

Are you legally permitted to work in the UK? * Select...

Do you have a current UK work permit? * Select...

Will you now or in the future require DRW to sponsor you in the UK? * Select...

How did you hear about this job? * Select...

Please provide additional detail if appropriate.

#J-18808-Ljbffr