Quantitative Researcher - Systematic

Quantitative research is a key driver of innovation at CTC and one of the pillars upon which our firm is built. We are seeking a Quantitative Researcher to partner with Trading and Technology to strengthen, scale, and evolve the firm's trading capabilities within one of the quant research teams. As a Quantitative Researcher, you will be embedded on a research desk, working close to the tip of the spear in a dynamic environment. This includes 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 the Quant team at CTC!

What You'll Do

• 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
• Conduct independent, high quality research in quantitative finance
• Communicate complex ideas and research results effectively, both in writing and verbally
• Drive innovation and results through analytical prowess and business acumen

What We're Looking For

• PhD in Science or Engineering fields (e.g. Statistics, Mathematics, Physics, Applied Mathematics, Operations Research, Electrical Engineering) strongly preferred
• Minimum 5 years of experience as a Quantitative Researcher in a top systematic trading team
• Demonstrable track record of generating positive PnL
• Advanced programming skills and experience with the software development lifecycle
• Proven ability to blend academic rigor with practical application in fast-paced trading environments
• Unwavering commitment to quality, coupled with a drive for delivering commercial outcomes
• Python skills including Numpy and Pandas libraries

Nice to Haves

• Experience with a wide variety of market and alternative data
• Expertise in US options markets, options pricing models, volatility surfaces, and risk management techniques
• Strong track record of publications in an industry setting