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.
The role is in Rates Data Analytics Quantitative Research team. The team's mission is to bring data-driven decision making and automation to the Rates business. The objective is to transform business practices, tools and infrastructure through data science.
The responsibilities of the role would be:
1. Understand the business processes and learn the relevant business workflows across different lines of businesses
2. Industrialize the availability of the data generated by the business workflows
3. Develop data-driven decision making analytics with demonstrable impact
4. Provide strong control environment around data access and model risk
The ideal candidate would have
- Quantitative experience in Fixed Income markets,
- Background in statistics and Machine Learning, or a strong STEM background with a demonstrable curiosity to learn Machine Learning
- Experience delivering production grade Python or C++ code.
- Knowledge of Haskell, OCaml, or other functional programming languages is a big plus, but not required.
- Experience with KDB is a big plus, but not required.
Req #: 180011487