Bring your expertise to JPMorgan Chase.  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.

As a Risk Management - Wholesale Credit Portfolio Analytics - Analyst within the Risk Management and Compliance team at JPMorgan Chase, you will be at the forefront of maintaining the strength and resilience of our firm. You will be instrumental 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. You will be part of the Wholesale Credit Risk – Portfolio Strategic Analytics team, developing value-added risk analytics solutions through advanced analytical frameworks and Machine Learning algorithms. Your role will focus on leveraging data and advanced ML methodologies to enhance the current End-to-End credit risk process across all of Wholesale.

 

Job responsibilities

Utilize Machine Learning methodologies, LLM and NLP techniques, and apply thoughtful quantitative, data science and analytical skills to solve complex business problems. Develop risk strategies that improve risk monitoring capabilities through using various source. Analyze structured/unstructured data from internal and external data sources to drive actionable insights in credit risk.   Lead development of event-driven scenario analytics to analyze the impact of macro-economic factors and current events on the Wholesale portfolio. Develop data visualization and summarization techniques to convey key findings in dashboards and presentations to senior management.

Required qualifications, skills and capabilities

Advanced degree in analytical field (e.g., Data Science, Computer Science, Engineering, Mathematics, Statistics) Excellent problem solving, communications, and teamwork skills. Experience across broad range of modern analytic and data tools, Python/Anaconda, TensorFlow and/or Keras/PyTorch, Spark, SQL. Desire to use modern technologies as a disruptive influence within Banking.

Preferred qualifications, skills and capabilities

Deep understanding and practical expertise and/or work experience with Machine Learning. LLM/NLP expertise or experience is strongly preferred.  Financial service background or Credit Risk experience preferred, but not required.  Experience working on Cloud is preferred.