Systematic Quantitative Researcher - PhD

About the role

Chicago Trading Company (CTC) is a premier proprietary trading firm specializing in options market making. Our collaborative culture fuels innovation in quantitative research, systematic trading strategies, and cutting-edge trading technology. For over three decades CTC has provided critical liquidity across derivatives exchanges worldwide - making them fairer, more transparent, and more efficient.

We strive to be the most innovative firm in the industry today, tomorrow, and long into the future while upholding ethical excellence. We believe that CTC makes a positive impact on the markets, the lives of our employees, and all the communities to which we belong. Started in 1995 by a team of forward-thinking Traders, we are proud to call ourselves an industry leader that keeps making markets and each other better.

The Role

Quantitative research is a key driver of innovation at CTC and one of the pillars upon which our firm is built. As a Quantitative Researcher, you'll operate near the tip of the spear in a collaborative, dynamic environment. This includes close partnership with other researchers, traders, and engineers on quantitative problem-solving, trading strategy generation, back-testing, statistical analysis, and system design.

Our environment of collaborative innovation and intellectual curiosity allows us to share in our victories while continually challenging ourselves to stretch the limits of our creativity. Take advantage of this opportunity to apply the scientific method to business problems as part of one of our Quant teams at CTC!

We prioritize team matching at the outset of our hiring process, thoughtfully considering which of our two teams (Vol Overlay or Delta Force) offers the best fit for each candidate's strengths and interests while also aligning to the firm's highest priority needs.

What We're Looking For

We are seeking a Quantitative Researcher who can seamlessly blend academic rigor with practical application in our fast-paced trading environment. This individual will partner with our Trading and Technology teams to strengthen, scale, and evolve the firm's trading capabilities. The ideal candidate will possess a unique combination of analytical prowess, programming skills, and eye for business, driving innovation and results in quantitative finance.

Responsibilities

• Analyze market data to come up with economic and microstructure hypotheses
• Build predictive and explanatory models to describe financial markets
• Add revenue by applying thorough research processes to real life business problems
• Contribute to ongoing improvement of research and trading infrastructure

Qualifications

• PhD in Science or Engineering fields (e.g. Statistics, Mathematics, Applied Mathematics, or Operations Research)
• Proven ability to conduct independent, high-quality research
• Exceptional ability to communicate complex ideas and research results, both in writing and verbally
• Unwavering commitment to quality, coupled with a drive for delivering commercial outcomes.
• Demonstrated expertise in applying quantitative modeling techniques to large, complex datasets
• Strong track record of publications in an industry setting
• Advanced Python programming skills

Nice to Have

• Proficiency in C++
• Experience in financial markets
• Experience using NumPy and Pandas libraries
• Experience with the software development lifecycle

Compensation

The salary range for this role is listed below. This role is also eligible for an annual discretionary bonus. The discretionary bonus will be dependent upon the individual's skills, experience, qualifications, and firm performance.

Salary Range $175,000—$200,000 USD

Use of Artificial Intelligence (AI)

Information submitted by job applicants may be subject to review and analysis by automated systems, including Artificial Intelligence (AI), as part of the recruitment process. Such systems are utilized to enhance the efficiency and effectiveness of our hiring procedures. Applicants are advised that any information provided may be evaluated by AI tools to ensure an equitable and thorough assessment.