Are you passionate about quantitative trading? Join a global team where your research and development skills will directly impact our systematic trading business. At JPMorganChase, you’ll collaborate with talented professionals, tackle complex challenges, and help shape the future of automated trading. This is your opportunity to make a meaningful contribution in a dynamic, fast-paced environment. Discover how you can grow your career and make a difference.

As a Vice President in Automated Trading Strategies (ATS), you will be part of a global team of quantitative traders responsible for designing, implementing, and running automated systematic trading strategies across asset classes. You will focus on the full stack of running a systematic trading book from alpha generation to execution and risk-management. In this role, you will use your research and development skills to implement strategies in production code and contribute to the day-to-day running of the business.

Job Responsibilities

Produce innovative research on quantitative trading strategiesUse data-driven techniques and backtesting to demonstrate performance improvementsImplement strategies in production code and enhance trading software systemsOptimize client pricing distributionMonitor performance and resolve day-to-day trading issuesCollaborate with other teams to identify opportunities for revenue growth

Required Qualifications, Capabilities, and Skills

Advanced degree (Master’s or PhD) in mathematics, physics, engineering, computer science, or other quantitative subjectAt least two years of industry experience or equivalent further academic studyStrong programming skills in C++, Java, or other object-oriented languagesKnowledge of probability, statistics, and experience with advanced data analysis techniquesExcellent written and verbal communication skillsActive interest in markets and quantitative trading

Preferred Qualifications, Capabilities, and Skills

Experience with FX quantitative trading or related asset classesFamiliarity with automated trading systemsExperience with large-scale data sets and optimising low-latency systems