- Development and support of equity, and equity hybrid models using options and futures.
- Systematic discovery of alpha signals using traditional and alternative datasets.
- Incorporate machine learning techniques into systematic strategy research and development.
- Help ensure that quantitative models, research tools and risk controls are adequate to support new product initiatives.
- Collaborate with other team members and other groups in order to drive productivity.
- Support technological infrastructure and analytical research function.
- Performs related duties as assigned.
- Minimum of 3-5 years’ experience in quantitative research and quantitative model development in any asset classes. Prior experience in the alternatives space is a huge plus for this role
- A graduate degree in a quantitative discipline (e.g., Financial Engineering, Econometrics, Computer Science, Engineering, Math, Physics).
- High-level proficiency in Python, R or similar programming languages. Demonstrated ability to write well-documented code.
- Previous hands-on experience in quantitative research, data science and predictive Modelling including machine learning is a huge plus.
- Demonstrated ability to learn and work with cutting-edge statistical methods and computational techniques.
- In-depth working knowledge of quantitative systems development, tools and engineering techniques including back testing, optimization, attribution, risk control and quality control.
- Knowledge of industry standard tools and databases such as Factset, Bloomberg, Worldscope, Compustat, IBES, Barra, etc.
- Ability to take ownership of projects, with a strong focus on quality and accuracy.
- A passion for investments combined with a strong work ethic, integrity, and a commitment to individual development.