About Us
We are a growing quantitative investment firm backed by experienced founders with deep expertise in systematic trading and capital markets. We are building a research-driven investment platform focused on innovation, scientific rigor, and scalable alpha generation. As the firm expands, we are seeking a Director of Quantitative Research to lead our research agenda and shape the future of our investment strategies. In this key leadership role, you will work closely with the founding partners to define investment direction, drive model development, and build out a high-performing research organization. This role is ideal for someone who is both hands-on and strategic — someone who wants to take ownership, influence firm-level decisions, and play a critical role in scaling a high-potential hedge fund.
Key Responsibilities
- Lead and oversee the end-to-end development of systematic, data-driven investment strategies.
- Drive research innovation in alpha signal generation, portfolio construction, risk modeling, and execution optimization.
- Establish scalable research frameworks, workflows, and best practices to support institutional-level growth.
- Work closely with trading, engineering, and operations teams to ensure seamless integration from research to production.
- Recruit, mentor, and develop a strong team of quantitative researchers and analysts.
- Clearly communicate research insights and investment rationales to internal stakeholders and leadership.
Qualifications
- Bachelor's, Master's, or PhD from a Top 20 U.S. University (as recognized by U.S. News rankings).
- 4–7 years of experience in quantitative research, systematic trading, financial modeling, or data-driven investment roles; buy-side experience strongly preferred.
- Advanced degree in Finance, Mathematics, Statistics, Physics, Computer Science, Engineering, or related quantitative disciplines.
- Proficiency in Python and SQL, with familiarity in machine learning frameworks (e.g., PyTorch, TensorFlow, scikit-learn).
- Demonstrated experience applying AI/ML approaches to factor modeling, time-series forecasting, signal discovery, or microstructure research.
- Strong strategic thinking, high professional integrity, and comfort operating in a dynamic environment.
- Excellent communication skills and ability to articulate complex reasoning clearly.