Quantitative Research Data Engineer: Vice President

As a Quantitative Research Data Engineering Vice President within our Wholesale Credit Data QR team, you will play a pivotal role in designing, analyzing, and delivering firm-wide data to support our Wholesale Credit Stress (CCAR, ICAAP, Risk Appetite) and Loan loss reserves models. You will focus on data model definition and the evolution of our Data Dictionary to enable deep dive data analysis and analytical explorations. You will have the opportunity to work on the evolution of our frameworks, underlying data platforms, and related tools to enhance the integration of pricing and forecast models, improve flexibility, extendibility of the framework, and improve scalability and performance. You will collaborate with experienced Wholesale Credit model developers and business partners, and have the chance to guide and mentor junior team members.

The role involves working in Risk Management and Compliance, where you'll be at the center of keeping JPMorganChase strong and resilient. You'll help the firm grow its business responsibly by anticipating new and emerging risks, and using expert judgment to solve real-world challenges impacting the company, customers and communities. The culture emphasizes thinking outside the box, challenging the status quo and striving to be best-in-class, all while maintaining a commitment to operating with integrity and discipline.

Key responsibilities include creating data pipelines, performing complex data transformations, conducting analysis for model development, and working with various stakeholders to understand and implement requirements for BASEL, CCAR, CECL and other credit risk models. You'll need strong technical skills in Python and SQL, along with deep understanding of data engineering principles and financial services domain knowledge.

This is an excellent opportunity for an experienced data professional who wants to make an impact in financial risk management while working with cutting-edge technologies and methodologies. The role offers the chance to work on challenging problems, mentor others, and contribute to critical risk management functions at a leading global financial institution.