One of the most advanced and highly rated Global Quantitative Equity Research teams is currently looking to add a researcher to their Hong Kong team.
You will be involved in developing new investment strategies, either by using existing data sources and innovative methods, or by exploring new data sources.
The candidate will focus on Quantitative Strategy and work on projects including, but not limited to, alpha generation through stock selection, factor modeling, portfolio construction, risk modeling and analysis.
The team would prefer someone who understands modern techniques in machine learning, signal processing and forecasting.
You should have a passion for understanding financial markets through empirical data analysis and modelling and be looking to apply this to the development of quantitative strategy.
Responsibilities will encompass researching and building multi-factor models for: equity portfolio construction, stock selection; Supporting and developing trading strategies for the business on a variety of products and Engaging with traders and marketing teams to deliver valuable insights.
In order to Apply you should have:
– Degree (master or PhD) in a quantitative domain, e.g., computer science, mathematics, physics, engineering, quantitative finance, etc.
– Good knowledge of statistics, machine learning and data science
-Good programming skills in R and/or Python; SQL
-Familiarity with quantitative research [e.g., stock selection, cross-asset quantitative strategies, portfolio optimization, alpha modeling]
The role will require experience working with large datasets using the latest machine learning applications to analyse investment opportunities in Global Equity Markets.
This position provides opportunities to do cutting-edge modeling as well as work on a bespoke basis with some of the most sophisticated teams in the world.
This is an excellent opportunity to join a team who a well-regarded, will offer excellent training and career progression.
In addition, there is a good salary package on offer.
In order to apply please send your CV to email@example.com