We're partnered with one of the world's largest alternative asset managers for a position based in NYC. The firm has over a trillion in AUM company wide, we're engaged with their multi-asset investing group with ~$80b in investor capital. The team generates attribution, performance, optimization, and risk analytics across their platform. This specific group sits within their multi-asset investing platform conducting research, designing, and implementing systematic investment strategies.
Responsibilities: Portfolio Analytics, Quantitative Research, and Data Infrastructure
- Maintain and develop internal data solutions focused on creating scalable and computationally efficient data and analytics infrastructure.
- Develop performance and portfolio analytics across attribution, portfolio construction, portfolio optimization, and risk modeling.
- Conduct research through using advanced stat and ML techniques using both conventional and alternative data. Alpha signal construction
- Work cross functionally with other multi-asset investing teams like ops, treasury, and legal.
Qualifications:
- 5+ years of experience in a quant research function or capacity
- Hands on experience leveraging advanced machine learning and statistical techniques.
- Python required, C++ beneficial.
- Master's or PhD in a quant discipline
- Applied experience in macro and asset class specific market data management.
- In-depth understanding of risk frameworks, risk models, portfolio optimization, alpha signal construction, and portfolio simulation
- Deep experience with analyzing large data sets.