My client are boutique investment team within a leading asset manager, looking to add a technically strong, experienced cross asset researcher for their QIS team. They provide liquid alternative investment solutions to a broad range of clients by forecasting risk and return across asset classes and a variety of risk premia.
The team utilizes these forecasts in developing and refining proprietary trading and asset allocation strategies which are implemented in portfolios with various objectives, including absolute return, dynamic multi-asset balanced and hedge fund replication. This is the chance to work in a dynamic trading and research environment in a team, which is smaller in comparison to their competitors meaning you will be closer to the action and be given the opportunity to make a real impact.
- Primary responsibility will support the internal research process to generate new strategies and optimize existing allocation methodologies
- Perform statistical and economic research to improve current investment strategies
- Conduct research on various aspects of the implementation of investment strategies such as trading cost models, risk models, optimization, and portfolio construction
- Explore new datasets and vendors
- Develop tools to improve automated functionality for monitoring, portfolio construction and research processes
- Prior experience of developing quantitative strategies and signals for a QIS like business
- Fluent in Python (Matlab or C++ also desirable)
- Strong work ethic, highly organized, detail oriented, and motivated to drive projects
- Strong written and verbal communication skills
- Motivation to work and perform under time sensitive environment in a fast paced environment
- Intellectual curiosity
- Strong quantitative skills with an advanced degree (PhD or Masters) from a leading academic institution