Quantitative Researcher (Machine Learning)

Location: Chicago, IL, United States; hybrid work with onsite attendance at the corporate office 3 or more days per week

Annual base salary: $150,000–$250,000, plus eligibility for a discretionary bonus.

Company

hirify.global is a quantitative trading firm founded in 1998, developing high-performance electronic trading infrastructure and systematic trading strategies through a global organization.

What you will do

• Create analysis tools to research trading opportunities from market data, including latency requirements, alpha horizons, and PNL impact.
• Develop, augment, and calibrate exchange simulators that faithfully replay market events.
• Research market microstructure and create high- to mid-frequency alphas from market data.
• Profile existing ultra-low-latency trading strategies and research, design, implement, and deploy new strategies.
• Create post-trade tools to monitor trading performance and competitiveness.

Requirements

• Bachelor’s degree or foreign equivalent in Mathematics, Statistics, Computer Science, or a related field.
• Five years of experience in a Quantitative Researcher, Quantitative Developer, or related position.
• Three years of experience with machine learning modeling.
• Experience with low-latency trading, mathematics and statistics, and machine learning techniques for large datasets.
• Knowledge of financial instruments and their derivatives.
• Knowledge of CME microstructures and market data protocols.
• Python for scientific computing.
• C++ for designing patterns and template metaprogramming.

Culture & Benefits

• Hybrid working opportunities with a collaborative, welcoming, and low-hierarchy workplace.
• Generous paid time off policies and regional savings plans and financial wellness tools.
• Free breakfast, lunch, and snacks daily.
• In-office wellness experiences, selected wellness expense reimbursement, company-sponsored sports teams, and fitness events.
• Volunteer opportunities, charitable giving, social events, and celebrations.
• Workshops and continuous learning opportunities.

Hiring process

• Applicants may apply through the posting and may also email a resume referencing job ID 00097686 to Tower HR.