Hybrid Quantitative Researcher - ML & Trading Signals

Two Sigma Investments, LLC.; New York (NY); Hybrid; USD 165,000 - 325,000; Full time

Benefits offered by this job

Discretionary bonus

Health insurance

Dental insurance

Wellness program

401(k) contributions

Job summary

Two Sigma Investments, LLC. is seeking a highly qualified quantitative researcher to design and implement predictive financial models using advanced statistical methods and machine learning.

The role focuses on developing production-quality Python code, building scalable data pipelines, and integrating models into live trading systems while performing rigorous back-testing and attribution analysis.

Qualifications

• Bachelor's degree in Mathematics, Statistics, Physics, or related quantitative field.
• Strong knowledge of Python and quantitative methods for research and production.
• Experience with time-series modeling, ML, and feature engineering.
• Publication or conference presentation demonstrating research ability (preferred).

Responsibilities

• Research, design, and develop predictive financial modeling systems using quantitative methods and ML.
• Build and back-test automated trading strategies with rigorous out-of-sample testing.
• Develop production-quality, scalable code and data pipelines.
• Integrate models into live trading systems and perform PnL attribution analysis.

Skills

Python

NumPy

Pandas

SciPy

Matplotlib

Scikit-learn

Time-series analysis

Linear algebra

Probability theory

SQL

Git

Education

Bachelor's degree in Mathematics/Statistics/Physics or related quantitative field

Tools

SQL databases

Git

Job description

Two Sigma Investments, LLC. is seeking a highly qualified quantitative researcher to design and implement predictive financial models using advanced statistical methods and machine learning.

The role focuses on developing production-quality Python code, building scalable data pipelines, and integrating models into live trading systems while performing rigorous back-testing and attribution analysis.