JPMorgan Quantitative Research - Equity Derivatives Group 

Zambia, Central Province 

845799465

As an Associate/ Vice President in the Quantitative Research Group, you will support the Asia Pacific Equity Derivatives business and perform a wide range of responsibilities covering model and payoff development to support existing and new client demands; trading, risk management and hedging automation and optimization; analyze and develop trading & hedging strategies. The team also acts as a culture carrier for modern data-driven business methods and brings data-driven decision making and automation to the Equity businesses.

The role consists in providing front-office modelling and risk-management support to equity trading desk (covering both Exotics and Flow).

Job Responsibilities:

• Developing and enhancing models for pricing and risk management of equity derivatives (variance/volatility payoff, parametric volatility models, risk-decomposition/replication/optimization)
• Analyzing the risks of complex derivatives portfolios
• Implementing new models / products in our quant library, writing model documentation and working closely with the technology team for model testing and deployment in production
• Providing day-to-day support to the trading desk: discussing new ideas, analyzing complex problems and providing solutions
• Develop data-driven decision-making tools by leveraging in-house core analytics and build fully automated systems with a high degree of quantitative optimization

Required qualifications, capabilities, and skills:

• A PhD or Master’s Degree in a quantitative discipline from a top-tier institution
• Minimum 3 years of relevant experience
• Excellent knowledge of derivatives pricing and risk management theory, vanilla options and volatility products
• Outstanding problem-solving abilities and communication skills
• Quantitative experience in the Equity business (volatility product modeling and hedging strategy), combined with a strong background in Mathematics/Engineering (ideally with knowledge in Stochastic Calculus, Probability theory, Financial Engineering)
• A strong coding background with proficiency in Python, C++, and relevant quantitative packages (numpy, pandas)
• Good expertise in statistical modelling including standard techniques, linear, convex & conic optimization
• Communicate skills and drive to engage with the business and bring cultural change towards a modern data-driven approach to business.