As a Quantitative Researcher, you will be engaged in impactful projects aimed at enhancing the specification and implementation of our investment models, as well as conducting research initiatives to improve decision-making in portfolio construction within our fully integrated, unified systematic investment process.
Responsibilities: Your responsibilities will evolve based on your experience and capabilities. Depending on your competitive advantages, you may be involved in the following typical tasks:
- Merging, structuring, and analyzing substantial volumes of data from diverse sources.
- Evaluating the quality of historical and current data, identifying deficiencies, and proposing corrective measures.
- Conducting ad-hoc exploratory statistical analysis across multiple large and complex data sets from various structured and unstructured sources.
- Developing and maintaining production-quality code directly utilized in the investment process.
- Investigating predictable patterns in asset returns, risks, trading costs, and other data relevant to financial markets.
- Conducting portfolio construction research using our simulation capability.
- Collaborating with software engineers to design feeds for new data sources from third-party vendors.
- Participating in data architecture decision-making to support the Research data platform.
Qualifications:
- Graduated from an undergraduate or graduate program in finance, mathematics, economics, or a closely-related discipline with a focus on quantitative and financial analysis.
- Demonstrated professional or academic success, with recent graduates encouraged to apply.
- Strong analytical, quantitative, and problem-solving skills.
- Understanding of probability, statistics, linear regression, time-series analysis, linear algebra, calculus, optimization, and portfolio theory.
- Knowledge of the application of statistics to economics, including econometrics or regression analysis.
- Experience with a statistical computing environment such as Python, Stata, R, or MATLAB.
- Experience analyzing large data sets.
- Understanding of finance, including equities and derivatives.
- Passion for financial markets.
- Excellent communication skills, including proficiency in data visualization.
- High energy and a strong work ethic.
Additional Considerations:
- Good understanding of the academic field of empirical asset pricing.
- Familiarity with financial data products.
- Experience with stock market data.
