Quantitative Researcher: ML-Powered Trading Models

Tradermath; Chicago (IL); Hybrid; USD 250,000 - 300,000; Full time

Benefits offered by this job

Health insurance

Dental insurance

Vision insurance

401k with employer match

Disability insurance

Life and AD&D insurance

HSA/FSA

Job summary

DRW, headquartered in Chicago, seeks a Quantitative Researcher to build mathematical models and automated trading strategies across asset classes. You will analyze market data, uncover relationships, and develop innovative research with access to strong compute resources and a collaborative team.

The role emphasizes independent exploration, rigorous statistics, and cutting-edge machine learning applied to real trading challenges in a fast-paced environment.

Qualifications

• Degree in a technical discipline with focus on statistics, ML, signal processing, optimization and control (Dec 2026–Aug 2027).
• Curiosity for model development and large data handling.
• Expertise in Python, R, MATLAB, or C++ for research.
• Strong communication to advocate for beliefs with the team.
• Hands-on experience applying ML to real-world problems.

Responsibilities

• Extract predictive signals from financial data using traditional statistics and ML.
• Assist software developers to translate research into production software.
• Optimize order execution and risk management of the trading system.
• Create robust solutions to problems in the trading environment.
• Formulate mathematical models to enhance strategies and research.
• Prototype algorithmic trades from ideas and automate decision-making.

Skills

Python

R

MATLAB

C++

Machine learning

Statistics

Education

Technical degree in statistics/ML/related

Tools

Python

R

MATLAB

C++

Job description

DRW, headquartered in Chicago, seeks a Quantitative Researcher to build mathematical models and automated trading strategies across asset classes. You will analyze market data, uncover relationships, and develop innovative research with access to strong compute resources and a collaborative team.

The role emphasizes independent exploration, rigorous statistics, and cutting-edge machine learning applied to real trading challenges in a fast-paced environment.