Our client is a top tier Investment bank looking to hire an experienced vol modelling quant.
Develop quantitative models for Institutional Equities Trading Platforms to facilitate effective Volatility Modeling and Risk Hedging.
Utilize statistical analysis including Data Mining and Reinforcement Learning methods to design and calibrate pricing and hedging models for Equities Trading.
Execute statistical analysis and perform back-testing to provide insight on trading flows.
Work closely with trading desks to analyze hedging performance on pre- and post-trade basis and to advise regarding business risk.
Collaborate with Technology on business requirements specifications, integration between platforms and quantitative models, and testing of trading systems. Serve as an equity derivatives model expert to provide guidance and documentation to trading and risk teams across the firm.
Minimum of Bachelor's degree in Statistics, Mathematics, Financial Engineering or closely related quantitative field - PhD degree preferred.
A couple of years' of experience implementing quantitative or statistical models - experience implementing quantitative or statistical models using C++ or Python.
Knowledge of Mathematics and optimization theory.
Knowledge of Linear algebra, probability, real and complex analysis, and time series analysis.
Experience performing statistical analysis, including likelihood estimation, hypothesis testing, principal component analysis, advanced data mining techniques, and data visualization on large datasets.
Technical writing in support of model development, documentation and evaluation using Latex.
Communicating mathematical and statistical concepts to non-technical audiences.