At Eclipse, we process hundreds of millions of data points per day, and the size and variety of data always grows. Our quantitative research team is based in our headquarters in Hong Kong, working where the decisions are made and have an opportunity to contribute directly to the bottom line.
The successful candidate will use our large amounts of internally and externally generated time series data and convert these to signals that help drive our trading and algorithms. The initial focus will be on predicting stock and futures short term moves.
Responsibilities and Duties
- Process and analyse large datasets to detect hidden signals and patterns in order to predict future events
- Perform quantitative analysis and modelling on the market to improve current trading strategies and develop new ones
- Take an idea from inception, through to detailed research, coding, and testing, and ultimately to production release
- Work independently yet closely with traders and IT staff
What you offer
- Masters or PhD in a quantitative discipline e.g. Statistics, Physics, Mathematics, Signal Processing, Machine Learning, etc
- 5+ years experience in analysing real-world data in a first-class research environment. Exposure to a variety of datasets would be an advantage. Experience in using machine learning to forecast sequence or time series data preferred
- 3+ years of financial markets experience working directly with trading desks, equities or futures preferred
- Very strong skills in writing production code in an OO programming language (prefer C++), and a statistical language (prefer Python), with the understanding of software development workflows required
- Experience working with low latency, real-time systems preferred
- Excellent communication skills
- Good command of spoken and written English
What we offer
- Exposure to a diverse range of technologies
- Excellent learning opportunities
- A work-life balance in a multi-cultural environment with reasonable work hours
All information provided will be treated in strict confidence and used solely for recruitment purposes.
Due to the high number of responses that we receive, we are only able to respond to successful applicants.