Quantitative Research Intern

DRW SINGAPORE PTE. LTD.; Singapore; Sur place; SGD 20 000 - 36 000; Plein temps

Résumé du poste

DRW SINGAPORE PTE. LTD. offers a Quantitative Research Intern role in Singapore, focusing on solving challenging trading problems using statistics, machine learning, and derivatives pricing concepts. You will work on non-latency sensitive opportunities across geographies with a team of researchers and traders.

The internship emphasizes hands-on research, back-testing, and development of research infrastructure, with mentorship and social activities in Singapore as part of the program.

Qualifications

• Pursuing a Bachelor's, Master's or PhD in a technical field with focus on Statistics, Optimization, ML, AI, Quantitative Finance graduating between December 2026 and August 2027.
• Strong Python programming experience with the Python ML stack.

Responsabilités

• Create practical solutions to problems presented in the trading environment on a systematic desk.
• Conduct statistical analysis of market data, trends and relationships across asset classes.
• Formulate and apply mathematical modeling and ML techniques to identify trading opportunities.
• Work closely with traders and researchers to build and refine research infrastructure and tools.

Connaissances

Python programming

Statistics

Machine Learning

Data analysis

Communication skills

Formation

Bachelor's/Master's/PhD in Statistics/ML/Quantitative Finance (graduating 2026–2027)

Outils

NumPy

Pandas

scikit-learn

Description du poste

Our formula for success is to hire exceptional people, encourage their ideas and reward their results.

As a Quantitative Research Intern you will have an opportunity to solve challenging problems arising in a trading environment while utilizing the latest statistical scientific algorithms, machine learning techniques and derivatives pricing theory.

The teams focus on non-latency sensitive investment opportunities and multi-asset class derivatives strategies across geographies. Our teams emphasize cutting-edge innovative scientific research and collaboration, allowing you to gain a deeper understanding of quantitative trading.

You will find great minds with diverse backgrounds, who are passionate about cultivating new ideas and exploring ways to bring them to life. You will use the team's custom research infrastructure for simulation, back-testing, and validation of the proposed models. While your days will have you engrossed with complex technology projects, your evenings will be spent exploring the city with organized social events to truly discover what it's like to live and work in Singapore.

How you will make an impact...

• Create practical solutions to problems presented in the trading environment on either a systematic equity trading desk or a fixed income options desk
• Conduct statistical analysis of market data, historical trends, and relationships across multiple asset classes
• Formulate and apply mathematical modeling, quantitative methods and machine learning techniques to identify and capture trading opportunities
• Work closely with traders and researchers to build and refine research infrastructure and tools

What you bring to the team...

• Are pursuing a Bachelor's, Master's or PhD in a technical discipline with a focus on Statistics, Optimization, Machine Learning, Artificial Intelligence, Quantitative Finance or related fields graduating between December 2026 and August 2027
• Proficiency in Python programming experience using the Python machine learning stack: numpy, pandas, scikit-learn, etc.
• Proficient programming skills with experience exploring large datasets
• Strong analytical and problem-solving skills including a solid foundation of statistics knowledge
• Working knowledge of probability theory, stochastic calculus and numerical algorithms such as finite differences, Monte Carlo simulation, etc.
• Some exposure to Natural Language Processing and/or High-Performance Computing is a plus
• Excellent written and verbal communication skills to report research results as well as methodologies
• Added bonus if you have been published in a top tier journal focusing on Natural Language Processing or High-Performance Computing

What to expect during the internship

• Meaningful projects: Each project, advised by a trader, promotes a comprehensive learning experience and provides you with real-world work experience.
• Community: Throughout the summer, we host a variety of educational, social and team‑building activities to explore the city, foster friendships and camaraderie.
• Mentorship: You'll build a professional relationship with an experienced mentor in your field. Mentors and mentees meet to discuss goals, challenges and professional development and explore the city together at our mentor outings.
• Education: As the trading industry continually evolves, both in terms of new products and transaction methods, the future will present us with unique opportunities and challenges. You'll complete an options course taught by an experienced trader and participate in a technology immersion course to better understand how technology and trading intersect.

About DRW

DRW is a diversified trading firm with over 3 decades of experience bringing sophisticated technology and exceptional people together to operate in markets around the world. We value autonomy and the ability to quickly pivot to capture opportunities, so we operate using our own capital and trading at our own risk.

Headquartered in Chicago with offices throughout the U.S., Canada, Europe, and Asia, we trade a variety of asset classes including Fixed Income, ETFs, Equities, FX, Commodities and Energy across all major global markets. We have also leveraged our expertise and technology to expand into three non-traditional strategies: real estate, venture capital and cryptoassets.

We operate with respect, curiosity and open minds. The people who thrive here share our belief that it's not just what we do that matters-it's how we do it. DRW is a place of high expectations, integrity, innovation and a willingness to challenge consensus.