Quantitative Research Intern: Build ML Models for Trading

Drweng; Chicago (IL); On-site; USD 250,000 - 300,000; Full time

Job summary

DRW is seeking a Quantitative Research Intern to tackle challenging problems in a trading environment, leveraging statistics, ML, and derivatives pricing theory. You’ll work with a team on non-latency sensitive opportunities across asset classes and gain exposure to research infrastructure, ML techniques, and back-testing.

Ideal candidates are pursuing technical degrees with graduation between December 2027 and August 2028, have Python ML stack experience, and strong communication skills for

Qualifications

• Pursuing a Bachelor’s, Master’s or PhD in a technical discipline with a focus on Statistics, Optimization, Machine Learning, AI, Quantitative Finance or related fields graduating between December 2027 and August 2028.
• Proficiency in Python programming with experience in the Python ML stack (NumPy, pandas, scikit-learn).
• Proficient programming with experience exploring large datasets.
• Strong analytical and problem‑solving skills with solid statistics knowledge.
• Knowledge of probability theory, stochastic calculus and numerical algorithms (e.g., finite differences, Monte Carlo).
• Some exposure to NLP and/or High‑Performance Computing is a plus.
• Excellent written and verbal communication to report results and methodologies.
• Bonus if published in top journals focusing on NLP or HPC.

Responsibilities

• Create practical solutions in a trading environment on systematic equity or fixed income desks.
• Conduct statistical analysis of market data and relationships across asset classes.
• Apply mathematical modeling and ML to identify and capture trading opportunities.
• Collaborate with traders and researchers to build and refine research infrastructure and tools.
• Engage in learning experiences and mentorship through structured projects.

Skills

Python programming

Statistics knowledge

Machine learning

Data analysis

Communication skills

NLP exposure

High-Performance Computing

Large dataset handling

Education

Bachelor’s/Master’s/PhD in Statistics/Math/CS

Tools

Python stack (NumPy, pandas, scikit-learn)

Monte Carlo simulation

Finite differences

NLP libraries

Job description

DRW is seeking a Quantitative Research Intern to tackle challenging problems in a trading environment, leveraging statistics, ML, and derivatives pricing theory. You’ll work with a team on non-latency sensitive opportunities across asset classes and gain exposure to research infrastructure, ML techniques, and back-testing.

Ideal candidates are pursuing technical degrees with graduation between December 2027 and August 2028, have Python ML stack experience, and strong communication skills for