IMC
Quantitative Researcher
$175K–$275K
Chicago, United States +3 · Full-time · Posted Oct 30, 2026
- Location
- Chicago, United States
New York, United States
Chicago, United States
New York, United States - Experience
- Two years in the job offered, a quantitative, technical, and mathematical role, or a related position; two years with each listed skill area.
- Education
- Bachelor’s degree or foreign equivalent in Computer Science, Financial Mathematics, Financial Engineering, Computational Mathematics, or a closely related quantitative, mathematical, or computational field.
About the job
Conduct quantitative research for proprietary trading by developing, testing, and validating models and algorithms, then coordinating their integration and evaluating their trading performance.
What you'll do
- Analyze market and trading data, formulate hypotheses, and develop quantitative models and trading strategies.
- Build research tools, simulations, visualizations, and backtesting frameworks; assess models for production readiness and performance.
- Lead research projects and collaborate with traders and developers; mentor graduate researchers and interns.
What they ask for
- Bachelor’s degree or foreign equivalent in Computer Science, Financial Mathematics, Financial Engineering, Computational Mathematics, or a closely related quantitative, mathematical, or computational field.
- Two years of experience in the job offered, a quantitative, technical, and mathematical role, or a related position.
- Two years of experience with each listed skill area, including quantitative analysis and model design, high-frequency financial data, financial theory, Python libraries, proprietary trading research, numerical optimization, options portfolios, and low-latency trading systems.
- Experience collaborating with traders and developers on quantitative research for a quantitative trading environment.
Pay
$175,000 — $275,000 USD (base salary)
Tools
Python, Pandas, NumPy, SciPy, scikit-learn, statsmodels, PyTorch, XGBoost
AI focus
Formulate trading hypotheses as machine-learning models and apply statistical learning methods to proprietary trading research.
Model-written summary · the original posting is authoritative