Global Stock Selection Researcher — Quant/ML

AQR Capital Management; Greenwich (CT); On-site; USD 225,000 - 245,000; Full time

Benefits offered by this job

Paid time off

Medical/Dental/Vision insurance

401(k)

Job summary

AQR Capital Management is seeking a talented Researcher to join our team focused on proprietary strategies related to global stock selection. You will conduct data ingestion and processing, analysis, and model implementation, collaborating with researchers, portfolio managers, risk managers and traders to improve investment strategies.

The role emphasizes hands-on research, building and evaluating models, and translating mathematical ideas into code while leveraging ML techniques and NLP tools

Qualifications

• B.S. degree in computer science, engineering, mathematics, statistics, operations research, physics or another quantitative discipline.
• 2-5 years’ experience in a data driven research environment with an alpha focus.
• Experience in quantitative research at a top asset manager or hedge fund preferred.
• Proficient programming in Python.
• Experience with machine learning libraries such as scikit-learn, TensorFlow or PyTorch; NLP/LLMs a plus.

Responsibilities

• Engage in alpha research and other quantitative analysis to improve current investment strategies.
• Perform statistical and economic research using traditional financial and alternative data.
• Build, train and fine-tune ML architectures for cross-sectional or time-series data.
• Develop features from raw data and evaluate their effectiveness.
• Collaborate with portfolio managers, risk managers and traders to implement ideas.

Skills

Python programming

Machine learning

NLP / LLMs

Data analysis

Education

B.S. in quantitative field

Tools

scikit-learn

TensorFlow

PyTorch

Job description

AQR Capital Management is seeking a talented Researcher to join our team focused on proprietary strategies related to global stock selection. You will conduct data ingestion and processing, analysis, and model implementation, collaborating with researchers, portfolio managers, risk managers and traders to improve investment strategies.

The role emphasizes hands-on research, building and evaluating models, and translating mathematical ideas into code while leveraging ML techniques and NLP tools