QS Investors is seeking an experienced quantitative analyst to enhance and support QS Investors’ suite of global equity investment strategies in New York. The ideal candidate will utilize their empirical research and practical implementation experience with a broad skill set that extends from market insight to quantification for historical validation to practical implementation to analyzing the contribution to live performance. Additionally, their experience with statistics/machine learning, as well as more traditional econometric techniques, will assist in applying these fields to strategy development.
The candidate should possess openness to new ideas, creative thinking and collaboration with other departments.
Key Responsibilities Include
- Supporting and enhancing current alpha forecasting models for global equities.
- Leading independent research projects by generating creative ideas and rigorous quantitative analysis that includes testing the efficacy of factors; identifying the industry-specific, macroeconomic and behavioral drivers of variability in factor performance; and writing robust production code.
- Participating in the development of the data infrastructure for investment management, looking for alternative and new sources of data, and ensuring the cleanliness and accuracy of data.
- Maintaining knowledge on current and emerging developments/trends, and identify and recommend new research ideas.
- Creating and communicating technical presentations, explaining our investment philosophy, strategy characteristics, and performance attribution to a wide variety of audiences.
- Enhancing existing reports and/or develop new solutions for analyzing portfolio exposures and attribution analysis so that PMs and product specialists can easily answer questions or write commentary around investment return and risk, market conditions, and the indicators and analytics used in QS’ models.
- Undertaking of ad hoc analytical projects as needed to support investment management, marketing and client services.
- Minimum 5 years of experience with global equity markets
- Superior quantitative skills with experience/training in data science, econometrics, finance, statistics, economics, or science/engineering fields
- Significant programming skills in Python, Matlab and/or other statistical packages such as R. SQL a plus
- Hands on experience with financial datasets such as Compustat, I/B/E/S, Datastream, Thomson Reuters Fundamentals, Worldscope, EDGAR
- Experience with Axioma, Barra or other risk modeling / optimization engine
- Market acumen
- Self-motivated with intellectual curiosity
- Attention to impressional accuracy and clarity of data visualizations
- Excellent written and oral presentation skills, able to explicate the theoretical underpinnings for model factors and weighting
- Well-developed interpersonal skills that foster a culture of teamwork and knowledge sharing