Description of the Company’s background
Ingold Capital is a CMS licensed fund management company. We focus on quantitative investment strategies, dedicated to producing exceptional returns for investors, by strictly adhering to mathematical and statistical methods, also through best-inclass risk management, compliance, and operations.
Job Description
We are seeking an experienced Hedge Fund Manager or Quantitative Researcher / Quantitative Strategist with expertise in machine learning and high-frequency trading (HFT). The ideal candidate will have a strong background in quantitative finance, a deep understanding of machine learning algorithms, and practical experience in managing trading strategies that drive consistent, high returns.
As part of the team, you will be responsible for developing, testing, and optimizing trading strategies for the Commodity Futures Market, Convertible Bond Market, Stock Market, and other asset classes. You will work closely with other researchers and traders to design and implement algorithmic trading models that deliver alpha and generate superior returns.
Job Requirements
Education:
- PhD in Computer Science, Finance, or a related field.
- Master’s or Bachelor’s degree in Computer Science, Mathematics, or a related discipline is also acceptable.
- Strong academic background in machine learning, reinforcement learning, and quantitative finance.
Experience:
- Hedge Fund/Quantitative Trading Experience: Minimum of 10 years of experience in a hedge fund or proprietary trading firm, with proven track record of managing trading strategies.
- Machine Learning & Data Science: Expertise in developing and implementing machine learning models for financial market prediction (e.g., price movement prediction, alpha generation).
- High-Frequency Trading: Experience in developing and optimizing high-frequency trading strategies is highly desirable.
- Strategy Development: Experience in developing profitable trading strategies in commodities, stocks, or other financial instruments.
- Programming Skills: Strong proficiency in Python, C/C++, and experience with algorithmic trading platforms and libraries (e.g., QuantLib, TensorFlow, PyTorch).
- Market Analysis: Ability to analyze market data and understand order book dynamics, price movements, and liquidity.
Technical Skills:
- Machine Learning Models: Expertise in supervised and unsupervised learning, reinforcement learning, deep learning, and their application to financial markets.
- HFT Strategy Development: Knowledge of high-frequency trading techniques, including low-latency data processing, algorithmic decision-making, and market microstructure.
- Linux Environment: Strong experience working in a Linux-based development environment.
- Data Analysis: Familiarity with data-driven decision making and financial modeling, using large datasets from financial markets.
BIPO Service (Singapore) Pte. Ltd.
EA License No. : 18S9180