J.P. Morgan's Quantitative Research Sales Analytics team aims to drive process efficiency and revenue generation improvements for the Fixed Income Sales organization through the deployment of data and analytics to better understand client behaviors, interests, and needs.
Requirements
- Proficiency in statistical methods including machine learning
- Strong Python programming skills
- Strong knowledge and experience in Derivatives pricing, Fixed Income and investment strategies
- Demonstrated experience applying statistical and/or machine learning techniques in the finance industry.
- Strong Python programming, including code architecture.
- Ability to manipulate and analyze complex, large scale, high-dimensionality data from varying sources
Responsibilities
- Work closely with Sales to build algorithms and workflows that enhance the way we service clients
- Innovate and evolve trade idea methods and workflows, leveraging a combination of diligent data analysis, traditional statistical reasoning, and advanced machine learning techniques
- Diligently architect and manage the evolution of the code base, including collaborating with other teams to maximize scale and leverage across the organization.
Other
- Exceptional communication abilities.
- Demonstrable years of professional experience in a similar role
- Strong academic degree (MSc or PhD, or equivalent) in a quantitative field (i.e. Mathematics, Physics, Statistics, Economics, Computer Science, etc.)
- Autonomy, excellent communication and strong motivation.
- Significant experience working in a quantitative group covering investment, structuring and/or trading businesses
