Head of Quantitative Research Talent Development

15 hours ago

Miami, Florida, United States Selby Jennings Full time

Firm Overview

The company is a global investment firm managing over $10 billion in assets. Founded in the mid-2000s, it has grown into a multi-strategy platform with a strong focus on volatility trading.

Its success is built on three key areas: strategy, technology, and people
.
The firm invests where it sees a clear advantage, using diversification and advanced tools to improve results. Its platform, developed over many years, supports all operations and adapts to changing markets. The company focuses on hiring and developing top talent, creating a culture that values independence, teamwork, and integrity.

Position Overview

The Head of Quantitative Research Development plays a critical role in supporting the firm's volatility business. This person strengthens quantitative capabilities and builds training programs for new talent. They work closely with volatility trading teams, researchers, and leadership to make strategies more systematic, apply machine learning, and mentor junior professionals.

Key Responsibilities:

  • Improve Quantitative Models:
  • Works with trading teams to upgrade models and introduce advanced research methods to groups with less quantitative focus.
  • Create and Lead Training Programs:
  • Designs a program for researchers and traders covering topics like data analysis, machine learning, and quantitative methods.
  • Mentor and Develop Talent:
  • Guides junior team members, offering feedback and support for technical and professional growth.
  • Collaborate Across Teams:
  • Builds strong relationships with portfolio managers, senior leaders, and HR to align training with business goals.

Qualifications:

  • Experience as a quantitative researcher, data scientist, or systematic trader at a top trading firm or hedge fund.
  • Strong understanding of
    options markets and volatility strategies
    .
  • Interest in building structured training programs in finance or data science.
  • Strong knowledge of quantitative methods and machine learning.
  • Ability to mentor and inspire junior talent.
  • Skilled at working with senior leaders and cross-functional teams.
  • Excellent organizational and communication skills.

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