IMC Trading Posted · from IMC Trading careers

Quantitative Researcher - Options

Chicago, United States
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About the role

IMC Trading is seeking a Senior Quantitative Researcher to join the options quant team. You will join the team as a senior member with the expectation of leading projects and mentoring juniors. Skills and responsibilities listed below.

Your Core Responsibilities:

  • Collaborate with the trading and quantitative research team to evaluate existing algorithms
  • Combine knowledge of systems, mathematical techniques and trading to identify the best places to improve our trading system
  • Rapidly research, test, and prototype new algorithmic ideas, preferably with Python.
  • See through the high-quality implementation of ideas to full-scale production trading.
  • Mentor graduate quantitative researchers

Your Skills and Experience:

  • Ms or PhD in a highly quantitative field
  • At least 5 years in financial services or a quantitative environment
  • Experience in project or people management
  • Strong programming skills, Python, Java or C++ preferred
  • Proven success in quantitative modelling and algorithm development
  • You have experience with options pricing

#LI-DNP

The Base Salary range for the role is included below. Base salary is only one component of total compensation; all full-time, permanent positions are eligible for a discretionary bonus and benefits, including paid leave and insurance. Please visit Benefits - US | IMC Trading for more comprehensive information.

Salary Range

$250,000—$300,000 USD

About Us

IMC is a research-driven trading firm where quantitative modeling, machine learning, and engineering shape how modern markets are traded. A stabilizing force in markets since 1989, we provide liquidity across trading venues, delivering the best outcome in value and risk management to investors. Using our own technology and capital, we build proprietary systems and algorithms that operate across global markets. Our researchers, traders, and engineers work as a collective, combining rapid experimentation, advanced infrastructure, and real-time feedback to turn insight into execution and execution into advantage.

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