Head of Quantitative Research, Investment Manager

The Quantitative Equity Group (QEG) is seeking a visionary and hands-on Head of Quantitative Research to lead the research function within our internal quantitative equity investing platform. This is a pivotal leadership role at a transformative moment for the platform which has established a strong foundation using traditional multi-factor quant models and is now poised to evolve into a next-generation investment engine leveraging more AI and machine learning approaches.

As a player/coach the incumbent will be responsible for (1) setting and executing the quantitative research agenda (2) building managing and mentoring a team of talented researchers and (3) contributing original research that enhances our quantitative equity investment strategies. The ideal candidate will bring deep expertise in quantitative equity research a strong grasp of machine learning and AI applications in finance and a passion for innovation and continuous improvement.

This role requires a strategic thinker with the ability to prioritize and build a high-ROI research pipeline while also rolling up their sleeves to develop and validate cutting-edge models. We are looking for someone with the demonstrated ability to encourage research creativity while managing projects to conclusion. The successful candidate will also collaborate closely with portfolio managers data scientists and software engineers to ensure research insights are effectively and systematically implemented in the investment process. This position reports to the Managing Director QEG.


WHAT YOU WILL DO:

Leadership Strategy & Team Management
Defines and drives the long-term research vision and strategy for the quantitative equity platform.
Prioritizes and manages a high-impact research agenda aligned with investment goals.
Serves as a thought leader in the integration of AI/ML into systematic equity investing.
Builds leads and mentors a high-performing team of quantitative researchers.
Fosters a collaborative and intellectually rigorous research culture.
Provides guidance and oversight on research design methodology and implementation.

Research & Innovation
Conducts original research to enhance alpha generation risk modeling and portfolio construction.
Explores and implements advanced techniques in machine learning and AI.
Ensures research is robust reproducible and scalable for production use.
Stays abreast of pertinent external research from industry practitioners and academics.


Collaboration & Implementation
Partners with portfolio managers data scientists and software engineers to translate research into actionable investment strategies.
Oversees the integration of research outputs into the investment platform and production environment.
Communicates research findings and strategy to key stakeholders and senior leadership.
Participates on committees and cross-team working groups.

WHAT YOU WILL BRING:

Required Education
Bachelors degree from an accredited four-year college or university with major coursework in a
technical or mathematical discipline including but not limited to mathematics statistics computer science financial engineering economics or a related area
A Masters degree in a related area may substitute for one (1) year of the required experience.
A Doctorate degree in a related area may substitute for two (2) years of the required experience.

Required Experience
Seven (7) years of full-time directly related progressively responsible experience in quantitative investment research or related experience.
Three (3) years of experience coordinating leading or supervising the work of others required.
Experience may be concurrent.

Required Registration Certification Licensure
None

Preferred Qualifications
Ten (10) years of full-time directly related progressively responsible experience in quantitative investment research.
Advanced degree (Ph.D. preferred) in a quantitative field such as mathematics statistics computer science financial engineering economics or a related area.
Proven leadership experience managing and mentoring research teams in a collaborative environment.
Demonstrated expertise in applying AI/ML techniques to financial data and investment problems.
Experience working in or with large institutional investors on the buy-side.

Knowledge of:
Mathematics probability and statistics or econometrics with an advanced level of understanding and application.
Theoretical and applied machine learning/AI expertise.
Traditional and alternative data sources relevant to quantitative investment research.
Traditional quantitative equity models including factor models risk models and portfolio
optimization with a deep and practical understanding of their design implementation and realworld application.
Financial markets with deep expertise in public equities and a strong grasp of their structure dynamics and investment implications.
Quantitative research methodologies investment strategies and platform architecture.

Skills in:
Using the Python data science stack to perform advanced quantitative research and analyses
(e.g. Pandas SciPy Numpy Scikit-Learn).
Manipulating large structured and unstructured data sets; navigating modern data architecture and cloud-based environments.
Maintaining code in a version control system (Git).
Managing and mentoring early- and mid-career quantitative investment professionals.
Making recommendations backed by rigorous research to key stakeholders and senior leadership

Ability to:
Prioritize and drive a high-impact quantitative research agenda.
Effectively manage a team of early- and mid-career quantitative researchers.
Communicate complex quantitative research topics to technical and non-technical stakeholders and senior leadership.
Autonomously manages quantitative research platform.