Are you looking for an exciting opportunity to join a dynamic and growing team in a fast paced and challenging area? This is a unique opportunity for you to work in our team to partner with the Business to provide a comprehensive view.

As a Climate Risk Associate within Risk Management and Compliance, you are at the heart of maintaining JPMorgan Chase's strength and resilience. You will play a crucial role in helping the firm grow responsibly by anticipating new and emerging risks, and using your expert judgement to solve real-world challenges that impact our company, customers, and communities. In Risk Management and Compliance, we challenge the status quo and strive to be best-in-class.

Job Responsibilities:

Analyze and interpret large datasets related to climate risk using Python and other analytical tools Develop and maintain methodologies for assessing and forecasting climate-related risk  Collaborate with cross-functional teams to integrate and align climate risk analytics with existing risk management processes across the firm Prepare reports and presentations to communicate findings and recommendations to internal stakeholders Stay updated on the latest developments in climate risk analytics and relevant regulatory frameworks

Required qualifications, capabilities, and skills:

BA/BS degree in Data Science, Statistics, Computer Science, or related field Proven experience in data analysis and modeling, working knowledge of data engineering fundamentals Proficiency in Python  Familiarity with data visualization tools and techniques, including GIS Strong analytic and problem solving skills, with attention to detail in process documentation and data validation Excellent communication skills with the ability to present complex information clearly and concisely 

Preferred qualifications, capabilities, and skills:

Knowledge of credit risk management and governance concepts Understanding of climate or environmental science and regulatory frameworks related to climate risk Advanced degree in quantitative/scientific field