Quantitative Researcher – Futures

Title: Quantitative Researcher – Futures Location: Chicago / Chicago, United States; New York, United States

Compensation (Salary Range): 250,000 – 300,000 USD per year

IMC is looking for experienced quantitative researchers to develop systematic futures trading strategies. Candidates will join a well-resourced effort combining IMC’s extensive options trading expertise with systematic strategies in the underlying futures market. Candidates will be responsible for performing large scale data analysis, utilizing modern machine learning techniques to derive forecasts that will be combined with IMC’s best-in-class technology platform for execution in futures markets.

Once on board, candidates will join a growing team that will be essential to all aspects of IMC’s trading. They will contribute not only to signal generation but also work w/ developers in design and implementation of a robust research framework that allows for new ideas to be researched, tested, and put into production in a timely manner.

Your Core Responsibilities:

• Conduct alpha / signal / feature research targeted at intraday futures trading strategies — from hypothesis generation through rigorous data analysis.
• Quickly prototype, backtest, and evaluate new trading ideas, using large-scale and high-frequency market data.
• Collaborate with developers, traders, and fellow researchers to design and implement a robust research-to-production pipeline. Once validated, see ideas through to full-scale deployment.
• Monitor and refine existing strategies, continuously evaluating performance, risk, and edge decay — and iterating to maintain or improve profitability.
• Explore and integrate new data sources, alternative data sets, and market microstructure signals to expand the research toolbox.
• Contribute to defining the strategic direction of research initiatives, including tooling, data infrastructure, and methodology improvements.

Your Skills & Experience:

• Advanced degree (MSc, PhD, or equivalent) in a quantitative or technical discipline (Mathematics, Statistics, Physics, Computer Science, Financial Engineering, or similar).
• Several years (5+ Years) of quantitative research experience, preferably in systematic trading, futures, HFT, or related high-frequency / high-throughput environments.
• Demonstrable track record of generating predictive signals in futures / derivatives / systematic trading.
• Excellent programming skills (e.g., Python, C++, or other relevant languages), and comfort working with large datasets and real-time data feeds.
• Strong statistical background, with experience in statistical modeling, time-series analysis, machine learning / ML-based approaches, and understanding of overfitting risk.
• Deep interest in market dynamics, high-frequency trading, and understanding of microstructure, order flow, and volatility — with an ability to translate that into actionable research.
• Strong analytical thinking, problem-solving skills, and a practical “business orientation”: able to assess strategy viability, robustness, and real-world performance.
• Excellent communication and collaboration skills — able to work effectively across teams (developers, traders, researchers).

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.