Quantitative Researcher

Required

• Applying statistical inference, optimization, regression analysis, time-series analysis, algorithm design, and other analytical and quantitative techniques to solve complex problems;
• Designing and implementing mathematical models and algorithms, including optimization, signal-generation, and statistical learning methods;
• Analyzing large-scale, high-frequency financial time-series datasets — including market data, order book data, trade data, and derived quantitative signals — to identify patterns, evaluate hypotheses, and measure model performance, with experience handling data quality issues such as gaps and outliers;
• Applying statistical inference, time-series analysis, and model-validation best practices to analyze data and evaluate quantitative research results;
• Applying concepts from financial theory, financial mathematics, and financial engineering, including market microstructure, derivatives pricing, risk modeling, and portfolio management;
• Experience collaborating with traders and developers conducting quantitative research for use in a quantitative trading environment;
• Using Python coding libraries, including Pandas, NumPy, SciPy, scikit-learn, statsmodels, PyTorch, XGBoost, LightGBM, Numba, Polars, Dask, Matplotlib to assist in quantitative analysis;
• Applying quantitative research methodologies for use in quantitative proprietary trading;
• Using numerical optimization techniques;
• Building options portfolios; and
• Developing trading systems that trade on low latency scale at the milisecond granularity.
• 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.