Head of Global Alpha Researcher (USA)

Posted 19 Days Ago
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Stamford, CT
Senior level
Machine Learning • Business Intelligence
The Role
The Head of Global Alpha Researchers will lead the Global Alpha Researcher Program, mentoring participants to develop Alpha Strategies. Responsibilities include executing the strategic vision for the program, overseeing research projects, and fostering collaboration. The ideal candidate should have a strong background in quantitative finance and leadership skills.
Summary Generated by Built In

Description

Trexquant developed the Global Alpha Researcher Program (GAR) in 2015 with a mission to provide a platform for highly academically-talented and high achieving individuals who may not have traditional finance backgrounds but are interested in applying their skills in quantitative finance. Since inception, the GAR program has contracted more than 200 individuals and many of GARs have converted to full-time employment at Trexquant. 

We are seeking a Head of Global Alpha Researchers to lead and expand the GAR program. In this role you will be responsible for leading our GAR alpha research initiatives, fostering a collaborative environment for participants across multiple regions and defining the roadmap to further grow the program. The ideal candidate will have a strong background in quantitative research, excellent leadership skills, and a passion for mentoring emerging talent.

Responsibilities

  • Lead and mentor Global Alpha Researchers in developing Alpha Strategies
  • Develop and execute the strategic vision for the GAR program, ensuring alignment with the company's goals and objectives.
  • Oversee the implementation of research projects and ensure the program’s curriculum are cutting-edge to the evolving landscape of quantitative finance
  • Attract, recruit and retain high-caliber researchers 
  • Provide mentorship and professional development to support the GARs growth and integration to the finance industry
  • Supervise and review research outputs, ensuring high standards of quality and innovation. 
  • Facilitate collaboration among GARs and proliferate GARs integration into Trexquant through the efficacy of their research and potential full-time employment.
  • Present strategic vision of the GAR program, assessment of individual GARs, and GAR program milestones, to Trexquant management.
Requirements
  • Bachelor’s, Master’s and or PhD degree in Math, Engineering, Statistical Modeling Computers Science or other related STEM field
  • Proven experience in quantitative finance, algorithmic trading, or a related field 
  • Demonstrate the ability to inspire and motivate researchers
  • Strong analytical and problem-solving skills with a track record of developing successful Alpha Strategies
  • Proficiency in Python programming and experience with machine learning techniques and data analysis tools
  • Creative and forward thinking mindset with a commitment to drive research excellence and fostering an environment collaboration and innovation
  • Previous leadership or managerial experience is a plus
Benefits
  • Competitive salary, plus bonus based on individual and company performance
  • Collaborative, casual, and friendly work environment while solving the hardest problems in the financial markets
  • PPO Health, dental and vision insurance premiums fully covered for you and your dependents

Top Skills

Python
The Company
HQ: Stamford, CT
67 Employees
Hybrid Workplace
Year Founded: 2012

What We Do

Being a quantitative finance firm that uses Machine Learning (ML) to create multi-asset portfolios and seek profit from the market, Trexquant has continuously improved its investment and research platform since starting operations, leveraging new and emerging technologies. Trexquant uses rigorous quantitative methods to create multi-asset portfolios in global markets. To do this, Trexquant develops trading signals using its vast and continuously growing collection of data variables used as inputs for more complex trading models called Strategies. The result is an ever-growing and adapting engine built from thousands of intricate models and tens of thousands of signals, tailor-made with the goal to outperform the market during any condition. Capital is managed across 5,500+ cash equity positions across the United States, Europe, Japan, Australia, and Canada.

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