JPMorgan Chase & Co. (NYSE: JPM) is a leading global financial services firm with assets of $2.6 trillion and operations worldwide. The firm is a leader in investment banking, financial services for consumers and small business, commercial banking, financial transaction processing, and asset management. A component of the Dow Jones Industrial Average, JPMorgan Chase & Co. serves millions of consumers in the United States and many of the world's most prominent corporate, institutional and government clients under its J.P. Morgan and Chase brands. Information about JPMorgan Chase & Co. is available at www.jpmorganchase.com.
Duties: Responsible for developing new equities and ETF market making strategies for JPMorgan’s Automated Electronic Market Making desk. Responsible for full life-cycle of quantitative strategy development, including idea generation using deep knowledge of equities market microstructure, mathematical finance, and market making principles; research and back-testing in Python using Big Data high frequency data sets and mathematical/statistical modelling; Implementation in a low latency C++ technology stack. Monitor strategy risk and behavior during trading hours and provide feedback to developers on areas of improvement and Post trade validation in Python comparing realized vs simulation outcomes. Utilize computer science skills to actively work with software developers in Technology team to translate mathematical models and trading logic into production quality C++ code. Provide software developers with detailed specifications for desired business logic, performing code reviews, providing feedback on code design and computation efficiency, and prioritizing project deliverables. Perform quality assurance on newly developed trading software by examining trading logs and verifying correct behavior of desk’s exchange bound orders. Build and maintain research and back-testing infrastructure in Python by utilizing open source (Numpy, Pandas) as well as in house APIs (Athena). Manage intraday and overnight risk and PnL of trading strategies using variety of tools.
Minimum education required: Master's degree or equivalent in Science, Technology, Engineering (any), Mathematics, or related quantitative field.
Minimum experience required: 3 years of experience in electronic equities trading experience, or related experience.
Skills required: Must have C++ software development experience. Must have nonlinear statistical modelling and optimization experience. Must have experience working with huge datasets in Python, R, or equivalent scripting language. Must have demonstrated US Equities market microstructure knowledge. Must have demonstrated knowledge of ETF pricing and index arbitrage. Must have experience with risk management and hedging tools. Must have demonstrated ability to generate novel trading signals based on large scale statistical analyses. Must have experience utilizing industry Dark Pools as well as exchange protocols.
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