Quantitative Researcher

2 weeks ago

Singapore CELESTIAL TECH PTE. LTD. Full time

We are looking for a **Quantitative Researcher**to join our core research team and help design, test, and refine data-driven trading models. This role is ideal for someone who combines strong statistical thinking, market intuition, and a deep interest in edge discovery through rigorous experimentation.

You will work closely with quant developers, data scientists, and traders to develop strategies that scale across a wide range of market conditions.

**Responsibilities**:

- Conduct rigorous research and statistical analysis to evaluate securities, market opportunities, and investment strategies.
- Analyze large, complex, and often high-frequency datasets to uncover trends and generate actionable insights.
- Develop and continuously improve mathematical models and algorithms for trading, risk management, or investment forecasting.
- Translate quantitative strategies into code and back-test models in live or simulated environments.
- Collaborate with traders, software engineers, and other research staff to implement and refine models.
- Prepare clear, concise research reports and presentations for both technical and non-technical audiences.
- Ensure data integrity, manage sensitive research data, and adhere to relevant compliance and ethical standards.

**Requirements**:

- Advanced degree (Master’s or PhD preferred) in Mathematics, Statistics, Physics, Computer Science, Engineering, or a related quantitative field.
- Strong programming skills in relevant languages such as Python, R, C++, or Matlab.
- Solid understanding of probability, statistics, and machine learning techniques (e.g., time-series analysis, pattern recognition, optimization).
- Demonstrable experience in statistical data analysis, hypothesis testing, and quantitative modeling.
- Excellent analytical, problem-solving, and communication skills.
- Ability to work independently as well as collaboratively within a research-driven team environment.
- Experience working in fast-paced, data-driven settings such as finance, trading, tech, or research is an asset.

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