Quantitative Researcher

Goliath Partners; New York (NY); On-site; USD 350,000 - 800,000; Full time

Job summary

Goliath Partners in New York is seeking a sharp Quantitative Researcher with experience across global equities and futures to lead innovative research within its stat-arb team. This rare opportunity invites you to explore how emerging AI techniques can enhance the investment process within an established systematic trading platform.

The successful candidate will work closely with portfolio managers, quantitative researchers, and engineers to identify valuable applications of LLMs, develop new

Qualifications

• Experience in quantitative research across systematic trading or applied AI.
• Strong foundations in statistics and time-series analysis.
• Proficiency in multi-factor model construction.

Responsibilities

• Research new approaches to extracting, structuring, and modeling information from large-scale datasets.
• Develop predictive signals and research tools for equities and futures strategies (intraday to minutes).
• Apply ML, NLP, and statistical modeling to improve forecasting, portfolio construction, and investment decisions.

Skills

Quantitative research

Time-series analysis

Multi-factor models

ML/NLP

Job description

A leading multi-strategy systematic fund is seeking a sharp Quantitative Researcher with experience accross global equities/futures to lead innovative research efforts within its stat-arb team.

This is a rare, high-ownership opportunity to explore how emerging AI techniques can enhance the investment process within an established systematic trading platform. The successful candidate will work closely with portfolio managers, quantitative researchers, and engineers to identify valuable applications of LLMs, develop new research capabilities, and translate promising ideas into measurable trading impact.

Compensation

• Base: $350K
• Total Comp: $800K-$xxM (based on experience/role)
• Structure: Base + Sign-on Bonus + P&L attachment + performance bonus

Role Description

• Research new approaches to extracting, structuring, and modeling information from large-scale structured and unstructured datasets.
• Develop predictive signals and research tools supporting mft (intraday to minutes) equities and futures strategies.
• Apply ML, NLP, and statistical modeling to improve forecasting, portfolio construction, and investment decision-making.
• Own projects from initial hypothesis and experimentation through validation, implementation, and live deployment.

Ideal Candidate

• Professional experience in quantitative research across systematic trading or applied AI.
• Strong foundations in statistics, time-series analysis, and multi-factor model construction