Graduate Quantitative Researcher; PhD
Listed on 2026-09-05
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Software Development
Data Scientist
As a Quantitative Researcher at IMC, your work will directly impact our global trading strategies. You will leverage your superior analytical, mathematical, and computing skills to improve existing models and develop new ones. We will empower you to discover your unique niche and excel, taking on responsibility and ownership from the start. Quantitative Researchers work closely Traders and Developers in an environment where problem solving, innovation and teamwork are recognized and rewarded.
YourCore Responsibilities:
- Apply rigorous analytical and quantitative techniques to solve complex problems
- Build custom tools to explore new research ideas
- Design mathematical models based upon trading ideas
- Implement and deploy new models into production
- Maintain best practices to keep our systems logical and consistent
Skills and Experience:
- Current university student graduating between September 2026 - July 2027 that is pursuing a PhD degree in Mathematics, Engineering, Statistics, Physics, Computer Science, or another highly quantitative field
- Has a passion for research and problem solving
- Approaches data analysis with rigorous thought processes and strong intuition
- Is a creative thinker who is driven and eager to solve challenging problems collaboratively
- Proficiency in a programming language (Python, C, C++, etc) is highly desired
- Must be available for full-time employment starting in February or August 2027
Base Salary: $250,000
About UsIMC 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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