Quantitative Researcher (Proprietary Trading)

Location: Chicago, United States or New York, United States; partial telecommuting permitted

Base salary: $175,000–$275,000 USD per year

Company

hirify.global is a research-driven proprietary trading firm that uses quantitative modeling, machine learning, and engineering to build systems and algorithms for global markets.

What you will do

• Evaluate, validate, and improve quantitative models used in proprietary trading strategies through statistical analysis, simulation, and empirical research.
• Design methods to analyze market data, trading statistics, and new data sources as the basis for trading strategies.
• Build research tools, simulations, visualizations, and backtesting frameworks to test hypotheses and measure model performance.
• Formulate mathematical, statistical, and machine-learning models, prototype algorithms, and coordinate integration with developers.
• Apply statistical inference, optimization, numerical methods, and financial mathematics to improve forecasting, pricing, execution, risk management, and trading performance.
• Lead research projects through hypothesis testing, validation, implementation planning, production readiness assessment, and post-deployment review; mentor graduate researchers and interns.

Requirements

• 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 offered role, a quantitative, technical, and mathematical role, or a related position.
• At least two years of experience applying statistical inference, optimization, regression analysis, time-series analysis, algorithm design, and other quantitative techniques to complex problems.
• At least two years of experience designing and implementing mathematical models and algorithms, including optimization, signal generation, and statistical learning methods.
• At least two years of experience analyzing large-scale, high-frequency financial time-series data, including market, order book, trade, and derived signal data, while addressing gaps and outliers.
• At least two years of experience applying model-validation practices and financial theory, including market microstructure, derivatives pricing, risk modeling, and portfolio management.
• Experience collaborating with traders and developers in a quantitative trading environment and applying quantitative research methodologies to proprietary trading.
• Experience using Python libraries including Pandas, NumPy, SciPy, scikit-learn, statsmodels, PyTorch, XGBoost, LightGBM, Numba, Polars, Dask, and Matplotlib.
• Experience using numerical optimization techniques, building options portfolios, and developing trading systems operating at millisecond granularity.

Culture & Benefits

• Full-time, permanent positions are eligible for a discretionary bonus.
• Benefits include paid leave and insurance.
• Researchers, traders, and engineers work collaboratively across quantitative research, technology, and trading.
• Multiple positions are available.