As a valued member of the Wholesale CRE Portfolio Analytics team, you will be responsible for the research and evaluation of commercial real estate market trends and economic impacts on a >$200 billion CRE portfolio. As part of Risk Management and Compliance, you are at the center of keeping JPMorgan Chase strong and resilient. You help the firm grow its business in a responsible way by anticipating new and emerging risks and using your expert judgement to solve real-world challenges that impact our company, customers and communities. Our culture in Risk Management and Compliance is all about thinking outside the box, challenging the status quo and striving to be best-in-class.

Job Responsibilities:

• Evaluate CRE data including portfolio concentrations, client and property financials, appraisal, macro-economic data, and real estate market trends and assess the impacts on loan performance and risk grading across all property types.

• Lead thematic and portfolio research initiatives focused on identifying and analyzing emerging risk trends. This involves synthesizing data and insights to understand how these trends impact industry dynamics and credit risk, thereby informing the development of proactive risk management strategies.

• Utilize strong Python and SQL skills to efficiently manage and manipulate large data from internal and external data sources to drive actionable insights in credit risk.

• Develop data visualization and summarization techniques to convey key findings in dashboards and presentations to senior management.

• Have a innovative mindset and look for ideas to identify leading indicators of portfolio performance, real estate market trends, economic demand drivers listed companies earnings call transcripts, news articles etc.

• (Optional) Apply Large Language Model (LLM) skills to synthesize information from multiple sources, generating systematic and comprehensive reports. This capability will enhance the ability to integrate diverse data points and insights into cohesive analyses that support strategic decision-making.

Preferred Qualifications:

• Deep Learning (neural network) and graph network expertise & experience is strongly preferred.

• Direct experience with analysis of commercial real estate is a plus.

Required Qualifications:

• Advanced degree in analytical field (e.g., Data Science, Computer Science, Engineering, Mathematics, Statistics).

• Deep understanding and practical expertise and/or work experience with Machine Learning, both supervised and unsupervised. Deep Learning (neural network) and graph network expertise & experience is strongly preferred.

• Experience across broad range of modern analytic and data tools, particularly Python, Alteryx, SQL, Tableau, Qliksense.

• Excellent problem solving, communications, and teamwork skills.

• Direct experience with analysis of commercial real estate is a plus.

• Desire to use modern technologies - should have the aptitude to use modern technologies to simplify and enhance analytics, and drive process efficiencies.