Deskripsi Pekerjaan
PT QuantEdge Capital Management, a leading quantitative investment firm based in Jakarta, is seeking a highly skilled and motivated Quantitative Analyst to join our dynamic team. In this role, you will be at the forefront of developing and implementing sophisticated mathematical models to drive our trading strategies and risk management frameworks. You will work closely with portfolio managers and software engineers to translate complex financial theories into robust, production-ready algorithms. If you are passionate about financial markets, possess strong programming skills, and thrive in a fast-paced, data-driven environment, we invite you to apply and help shape the future of quantitative finance in Southeast Asia.
Tanggung Jawab
- Design, develop, and backtest quantitative trading strategies using statistical and machine learning techniques.
- Analyze large financial datasets to identify market inefficiencies and generate alpha signals.
- Build and maintain robust risk management models to monitor and mitigate portfolio exposure.
- Collaborate with software engineers to integrate quantitative models into the firm's automated trading infrastructure.
- Conduct rigorous research on market microstructure and macroeconomic factors affecting asset pricing.
- Prepare detailed reports and presentations on model performance and market insights for senior management.
- Stay abreast of the latest academic research and technological advancements in quantitative finance.
- Optimize existing algorithms for execution speed and computational efficiency.
Kualifikasi
- Bachelor’s or Master’s degree in Mathematics, Physics, Statistics, Computer Science, Financial Engineering, or a related quantitative field.
- Proven experience (2+ years) in quantitative research, algorithmic trading, or financial modeling.
- Strong proficiency in Python (NumPy, Pandas, SciPy) and at least one compiled language such as C++ or Java.
- Deep understanding of statistical analysis, time-series analysis, and stochastic calculus.
- Experience with machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn) is highly preferred.
- Excellent problem-solving skills and a strong attention to detail.
- Ability to communicate complex quantitative concepts to non-technical stakeholders.
- Familiarity with financial markets, derivatives pricing, and portfolio theory.