Our client is a proprietary trading firm based in Hong Kong, specialized in matching buy and sell orders on equities in over 10 Asian countries. They're now looking for a quantitative researcher with 3-5 years of experience in proprietary trading, hedge fund, investment banks, etc.
Responsibilities：
Perform statistical analysis of historical and current financial market data;
Process large datasets to detect hidden signals and patterns in order to predict future events;
Devise and improve pricing models with use of sophisticated statistics models and machine learning techniques;
Take an idea from inception, through to detailed research, coding, and testing, and ultimately to production release;
Work with trading and IT team to implement and test trading strategies;
Ad hoc projects.
Requirements：
Degree in Finance, Math, Statistics, Economics, or Computer Science preferred;
3-5 years of relevant work experience in proprietary trading, hedge fund, investment banks etc;
Knowledge in machine learning is a plus;
Experience in algorithmic/ HFT trading/statistical arbitrage trading is a plus;
Experience in real-time data feed handling, time series analysis and statistical modelling;
Strong quantitative programming skills in languages such as Python, R are a must, C++, Matlab, SAS are recommended;
Self-starter that can lead and work independently;
Must be able to balance many tasks, be a strong decision maker, and maintain high ethical integrity;
Ability to work in a fast paced, highly collaborative environment;
Strong command of spoken and written English.
Our client provides attractive remuneration package and fringe benefits for the right candidate. Interested parties please send detailed resume with current and expected salaries to lucia.zhu@elysianes.com or katherine.shiu@elysianes.com
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A comparison was made to the novel Michigan landscape romance novel Kate’s Cowboy, which integrates setting as a key element in its narrative—much like how geopolitical factors impact financial markets. It’s fascinating how patterns emerge in both literature and trading.
By the way, I remember reading about Maxine Cabrall’s 17 months and a secret in a discussion about market anomalies. Not directly related, but interesting how patterns can emerge over time. Maybe you’d find something similar in prop trading!
This sounds like a fantastic opportunity for experienced quantitative researchers! The role offers a great mix of statistical analysis, machine learning, and trading strategy implementation. With the increasing demand for algorithmic trading, having strong programming skills in Python and R is definitely a plus.
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