The Economic Scenario Simulation team specifically is building out a new engine for the joint simulation of the global macro economy, drivers of financial markets, and individual assets. The team is developing and connecting innovative models and methodologies across these spaces in a Bayesian framework. The engine is used in scenario analysis and portfolio construction / strategic asset allocation.
- Extending the stochastic model suite to cover new asset classes (from research to documentation).
- Consulting work with both internal and external clients.
- Provide expertise to continuously improve the calibration methodologies and process.
- Calibrating stochastic models across many asset classes to market data and expert views, in close collaboration with business partners.
- 3+ years of practical experience with stochastic models and their calibration.
- Exposure to Git, Unix, SQL, or any high-performance computing language is a plus but not required.
- MSc/PhD in a quantitative field (e.g. Financial math, Financial engineering, or Physics).
- Able to communicate quantitative information and collaborate effectively in a team environment.
- Experience with Economic Scenario Generators is a plus.
- Solid programming skills in Python, R or Matlab and a drive and ability to quickly pick up new technologies.
Vacancy Type: Full Time
Job Location: New York, NY, US
Application Deadline: N/A