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The Emerald Recruiting Group

Managing Director Quantative Research Manager

The Emerald Recruiting Group, New York, New York, us, 10261

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Our client, a

leading global hedge fund , is seeking a

Quantitative Research Manager – Equities

to lead a team of researchers developing and deploying systematic equity strategies across global markets. This is a front-office, hands-on leadership role for a seasoned quant who knows how to move from model design to live execution—and build teams that do the same.

You’ll guide a group of researchers and developers focused on

alpha generation, portfolio construction, and execution optimization

within a sophisticated, data-rich environment. This is an opportunity to shape strategy architecture, mentor next‑generation talent, and deliver measurable performance in one of the industry’s most respected systematic platforms.

What You’ll Do

Lead a team of

quantitative researchers and data scientists

focused on alpha research across equities (stat‑arb, factor, and multi‑horizon).

Oversee

signal discovery, model validation, and productionization

of new trading ideas.

Manage

end‑to‑end research pipelines —from data sourcing and feature engineering to backtesting and live performance monitoring.

Collaborate closely with

portfolio managers, engineers, and traders

to refine models and drive real P&L impact.

Evaluate and implement new

machine learning, NLP, and alternative data techniques

to uncover differentiated signals.

Guide research into

execution algorithms, transaction cost modeling, and portfolio optimization.

Develop and enforce best practices for

data integrity, version control, and model documentation.

Provide strategic direction, mentorship, and technical guidance to a high-caliber quant team.

What You Bring

8–12+ years

of experience in

quantitative research or systematic equities trading , including team leadership.

Proven record developing and deploying alpha models that have demonstrated live profitability.

Deep understanding of

market microstructure, equity factors, and portfolio construction methodologies.

Expertise in

Python, C++, R, or MATLAB , and familiarity with distributed computing frameworks.

Advanced degree (PhD or Master’s) in

Applied Mathematics, Physics, Computer Science, or Financial Engineering.

Strong grasp of

machine learning, statistical inference, and time-series analysis.

Excellent communication skills—able to translate research outcomes into actionable trading insights.

Entrepreneurial mindset and collaborative leadership style.

Why It’s Worth a Conversation

Opportunity to

lead a world‑class quant research team

with autonomy, resources, and scale.

Exposure to

multi‑billion AUM trading infrastructure , global data sets, and elite engineering support.

Collaborative, performance‑driven culture that rewards innovation and measurable results.

Competitive compensation with

P&L participation and leadership upside.

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