Quantitative Researcher: ML-Driven Trading Strategies

DRW SINGAPORE PTE. LTD.

Singapore

On-site

SGD 120,000 - 180,000

Full time

4 days ago
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Job summary

DRW Singapore is seeking a Quantitative Researcher to develop mathematical models using advanced statistical learning methods and to build automated trading strategies across multiple asset classes. You’ll collaborate with a team of researchers, traders and software developers while gaining access to clean data and compute resources.

The role emphasizes independent exploration, practical research results, and experimentation with machine learning, signal processing and optimization to uncover

Qualifications

  • Graduating between December 2026 and August 2027 in a technical field (Bachelor/Master/PhD).
  • Curiosity for model development and handling large data sets.
  • Proficiency in Python, R, MATLAB or C++ for research.
  • Strong problem-solving and statistical skills.
  • Ability to take the lead on assignments and deliver practical results.

Responsibilities

  • Extract predictive signals from financial data using statistics and ML techniques.
  • Assist software developers to translate research strategies into production software.
  • Optimize order execution and risk management of our trading system.
  • Create robust solutions to problems presented in the trading environment.
  • Formulate mathematical modeling techniques to enhance trading strategies and research.
  • Automate human-decision trading strategies; prototype algorithmic trades.

Skills

Python
R
MATLAB
C++

Education

Degree in technical discipline (Bachelor/Master/PhD)

Job description

DRW Singapore is seeking a Quantitative Researcher to develop mathematical models using advanced statistical learning methods and to build automated trading strategies across multiple asset classes. You’ll collaborate with a team of researchers, traders and software developers while gaining access to clean data and compute resources.

The role emphasizes independent exploration, practical research results, and experimentation with machine learning, signal processing and optimization to uncover

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