Quant Researcher

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

Hightly 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.