Quant Researcher

Location: New York, NY (Metro Area)

About the Opportunity Join a pioneering investment firm at the intersection of advanced machine learning and systematic trading. We have developed a proprietary, automated "Alpha Factory" that is already live-trading, and we are now seeking a visionary Quantitative Researcher to serve as the foundational architect for our strategy discovery engine. In this high-impact role, you will act as a "Player-Coach" for our technology—simultaneously developing high-sharpe signals while systematically codifying your research intuition into our autonomous AI infrastructure.

Responsibilities

• Systemic Mentorship: Guide the evolution of a self-learning trading engine by translating complex quantitative intuition into automated research workflows.
• Alpha Generation: Design, backtest, and deploy innovative predictive signals across diverse asset classes to drive firm P&L.
• Infrastructure Optimization: Collaborate with core engineering teams to refine the "Alpha Factory," ensuring the system can autonomously identify, validate, and execute new trading ideas.
• Feedback Integration: Analyze system performance and "teach" the AI to recognize and avoid false signals, improving the overall autonomy of the discovery pipeline.
• Strategic Leadership: Serve as a subject matter expert on market microstructure and quantitative modeling to steer the firm’s long-term research roadmap.

Requirements

• Proven Track Record: Extensive experience in systematic alpha research within a hedge fund or high-frequency trading environment.
• Expert Programming: Advanced proficiency in Python, C++, or similar languages, specifically applied to large-scale data analysis and modeling.
• Mathematical Excellence: Deep understanding of statistics, machine learning, and financial econometrics.
• Architectural Mindset: Experience not just in finding signals, but in building the frameworks and tools that facilitate signal discovery at scale.
• Academic Background: Advanced degree (Master’s or PhD) in a quantitative field such as Physics, Mathematics, Computer Science, or Engineering.

Preferred Qualifications

• Experience with reinforcement learning or LLMs applied to financial time-series data.
• Prior experience at a "founding" or early-stage systematic firm.
• Knowledge of cloud-native high-performance computing (HPC) environments.

Compensation & Benefits

• Highly competitive base salary and performance-based bonus.
• Significant equity/founding member participation.
• Comprehensive health, dental, and vision insurance.
• Professional development budget and flexible work arrangements.

We are an equal opportunity employer and value diversity at our company. We do not discriminate based on race, religion, color, ethnic origin, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.