Quantitative Researcher

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

Position Summary

Job Location: 100 Avenue of the Americas, New York, NY 10013

Note: Company "Hybrid" work attendance policy: In-office work attendance required at the aforementioned office address for collaboration days based on each team's requirement; telecommuting/working from home is permissible for remainder of the same month.

Duties:

Research, design, and develop predictive financial modeling systems using advanced quantitative methods, statistical analysis, and machine learning to forecast asset returns and inform trading decisions. Perform exploratory data analysis and feature engineering on market and alternative datasets, applying techniques including regression, time-series and panel modeling, and pattern recognition to identify and validate alpha signals. Build, back-test, and rigorously validate automated trading strategies in Python with robust out-of-sample testing and walk-forward analysis. Develop production-quality, high-reliability, and efficient code and computational libraries to accelerate research workflows. Design scalable, distributed data processing pipelines for data ingestion, feature computation, model training, and evaluation. Integrate models into live trading systems, conduct PnL and attribution analysis, investigate anomalies, and implement monitoring and alerting.

Minimum education required:

Bachelor's Degree in Mathematics, Statistics, Physics, or related quantitative field.

Skills required:

Must have knowledge of the following quantitative skills and technologies: Python programming for research and production, including scientific computing libraries (NumPy, SciPy, Pandas, Matplotlib, and Scikit-learn); mathematics and statistical analysis, including linear algebra, probability theory, multivariate regression methods, and time-series analysis; machine learning model development and tuning; data science techniques including cleaning, processing, and analyzing large, high-dimensional datasets; parallel and distributed computing for computationally intensive research; SQL databases for data storage and querying; version control software (git) for collaborative code development; and quantitative research ability, as evidenced by publication of research in peer-reviewed academic journal(s) or presentation at academic conference(s). Must also pass company's required skills assessment.

Base salary:

The base pay for this role will be between $165,000 and $325,000 per year. This role may also be eligible for other forms of compensation and benefits, such as a discretionary bonus, health, dental, and other wellness plans and 401(k) contributions. Discretionary bonus can be a significant portion of total compensation. Actual compensation for successful candidates will be carefully determined based on a number of factors, including their skills, qualifications, and experience.

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