We are looking for Quantitative Researchers to join our Research group. We are a collaborative, data-driven, intellectually rigorous team responsible for coming up with investment ideas, codifying those ideas into signals, back- testing the signals, and producing return, risk and trading cost forecasts based on the signals to drive trading decisions. We maintain a friendly, team- oriented environment and place a high value on professionalism, attitude and initiative.
As a Quantitative Researcher, you will work on high-impact projects that improve the specification and/or implementation of our investment models as well as research projects that improve portfolio construction decisions in our fully integrated, unified systematic investment process.
Your responsibilities are expected to grow in line with your experience and abilities. Depending on your competitive advantages, typical responsibilities may include:
Merging, structuring, and analyzing large amounts of data from various sources
Assessing the quality of historical and current data, diagnosing deficiencies, and prescribing fixes
Performing ad-hoc exploratory statistical analysis across multiple large complex data sets from a variety of structured and unstructured sources
Writing and maintaining production-quality code used directly in the investment process
Researching predictable patterns in asset returns, risks, trading costs and other data relevant to financial markets
Performing portfolio construction research using our simulation capability
Working 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
Enrolled in or graduated from an undergraduate or graduate program in finance, mathematics, economics, or a closely-related discipline emphasizing quantitative and financial analysis.
Demonstrated professional or academic success (recent graduates are 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 data visualization
High energy and strong work ethic
In addition, the following are a plus:
Good understanding of the academic field of empirical asset pricing
Familiarity with financial data products
Experience with stock market data sets
We maintain a friendly, team-oriented environment and place a high value on professionalism, attitude and initiative.