I am currently working with a $30BN AUM Hedge Fund in New York that is looking to expand one of their PM pod teams focusing within the Index Rebalance space. They are looking for an exceptionally strong Quantitative Researcher to assist the PM in developing, implementing, and optimizing key models, trading strategies, and algorithms utilizing advanced statistical techniques. This is a fantastic opportunity to sit within an extremely collaborative, fast-paced environment where you will be able to directly work alongside one of the most successful Index Rebal PMs in the industry!
Responsibilities:
- Conduct research and analysis to develop quantitative models and algorithms for Equity Index Rebalance strategies.
- Collaborate with the PM and other team members to identify and implement innovative investment strategies.
- Design, backtest, and optimize trading algorithms using historical data and advanced statistical techniques.
- Develop tools and infrastructure to support quantitative research and trading activities.
- Monitor and analyze market data and trends to identify new opportunities and refine existing strategies.
- Stay current with developments in financial markets, quantitative research, and technology, and incorporate new ideas and technology into the investment process.
Qualifications:
- 2+ years of experience working on conducting research, development, and optimization of Index Rebalance strategies.
- Advanced degree (Ph.D. or Master's) in a quantitative field such as Mathematics, Statistics, Computer Science, Physics, Engineering, or Finance.
- Strong quantitative and analytical skills, with a deep understanding of statistical methods and financial modeling.
- Proficiency in Python programming with experience in data analysis and machine learning libraries.
- Knowledge of financial markets, equity index products, and quantitative trading strategies.
- Experience working with large datasets and time-series analysis.
- Excellent communication and collaboration skills, with the ability to work effectively in a fast-paced, team-oriented environment.
