Head of Quantitative Research, Investment Manager
AUSTIN, TXPosted 30+ days ago
Job summary
Job post source
This job is directly from Teacher Retirement System of Texas
Job overview
The Head of Quantitative Research, Investment Manager leads the quantitative equity research function to innovate and enhance investment strategies using AI and machine learning, impacting the management of a $200 billion portfolio.
Responsibilities and impact
The role involves setting research strategy, leading and mentoring a research team, conducting original quantitative research, integrating AI/ML techniques, collaborating with portfolio managers and engineers, and implementing research into investment processes.
Compensation and benefits
Compensation depends on qualifications; no specific details on bonuses or benefits are provided.
Experience and skills
Requires a bachelor's degree in a quantitative field, seven years of related experience with leadership responsibilities, and expertise in quantitative equity research, AI/ML applications, Python, and managing research teams; advanced degrees and buy-side experience are preferred.
Career development
Opportunities include leading a transformative research platform, mentoring a high-performing team, and working at a large institutional investor with exposure to cutting-edge quantitative finance.
Work environment and culture
The company values diversity, innovation, collaboration, and intellectual rigor in a supportive environment focused on public service and financial stewardship.
Company information
Teacher Retirement System of Texas manages over $200 billion in public and private investments for 2 million public education employees and retirees in Texas, emphasizing trust and financial future impact.
Team overview
The candidate will join the Quantitative Equity Group within the Multi-Asset Strategies Group, working closely with portfolio managers, data scientists, and software engineers, reporting to the Managing Director.
Job location and travel
Position is located at 1900 Aldrich Street, Austin, Texas, with no mention of remote work or travel requirements.
Application process
Applicants are encouraged to apply before the closing date 10/9/2025 via the TRS career website, with contact available for veterans and additional information.
Unique job features
This role uniquely combines leadership and hands-on research at a pivotal moment transitioning to AI/ML-driven investment strategies in a large public pension fund.
Company overview
The Teacher Retirement System of Texas (TRS) is a public pension fund established in 1937 to provide retirement and related benefits to employees of public schools, colleges, and universities in Texas. TRS makes money primarily through contributions from members and employers, as well as investment earnings from its diversified portfolio. With over $160 billion in assets, it is one of the largest public pension funds in the United States. Key historical milestones include the expansion of benefits and the implementation of various investment strategies to ensure long-term sustainability.
How to land this job
Position your resume to highlight leadership in quantitative research, especially your experience setting research agendas and managing teams, as this role requires strategic vision and team mentorship.
Emphasize your expertise in AI and machine learning applications in finance, showcasing any relevant projects or knowledge in integrating these techniques into investment strategies.
Apply through multiple channels including the Teacher Retirement System of Texas official careers page and LinkedIn to maximize your application visibility.
Connect with professionals in the Multi-Asset Strategies Group or Investment Management Division on LinkedIn; use ice breakers like commenting on recent quantitative research trends or asking about the integration of AI in their investment processes to start conversations.
Optimize your resume for ATS by including keywords from the job description such as 'quantitative research,' 'machine learning,' 'AI,' 'portfolio construction,' 'Python,' and 'team leadership' to ensure it passes automated screenings.
Utilize Jennie Johnson's Power Apply feature to automate tailored applications, find multiple application portals, and identify LinkedIn contacts for networking, allowing you to focus your energy on preparing for interviews and refining your skills.
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