Liquidity Risk Management - Data Analytics Lead - Vice President

Join JPMorgan Chase and help shape the future of risk management. As a leader in our Risk Management and Compliance team, you'll be at the forefront of developing advanced analytics and automation solutions that keep our firm strong and resilient. Collaborate with top talent, challenge the status quo, and make a tangible impact on our business, customers, and communities. If you thrive in a culture of innovation and excellence, this is your opportunity to grow and lead. Bring your expertise and help us set new standards in liquidity risk oversight.

As a Liquidity Risk Management - Data Analytics Lead - Vice President in the Liquidity Risk Management (LRM) team within Treasury/Chief Investment Office (T/CIO), you will partner with risk managers to design, build, and implement data-driven solutions that enhance our liquidity risk management capabilities. This role offers the opportunity to drive automation, efficiency, and innovation in risk oversight, leveraging your technical and analytical expertise to solve complex challenges and support the firm's strategic objectives.

Job Responsibilities:

• Develop, test, and deploy advanced data models, tools, and analytics for liquidity risk assessment and management.
• Write efficient, production-quality Python code for data analysis, automation, and integration tasks.
• Integrate and process data from internal and external APIs to support risk monitoring and reporting.
• Engineer new processes and re-engineer existing workflows to enable straight-through processing and reduce operational risk.
• Design and implement "human-in-the-loop" controls for oversight and decision-making in automated processes.
• Collaborate with risk managers, technology teams, and stakeholders to gather requirements and deliver effective solutions.
• Document methodologies, code, and processes to ensure transparency and reproducibility.
• Monitor and report on liquidity positions, stress tests, regulatory metrics, and funding activities.
• Independently review liquidity management processes for adequacy and effectiveness.
• Establish and monitor liquidity risk metrics, limits, and indicators.
• Support compliance with internal and regulatory liquidity requirements.

• Bachelor's or Master's degree in Computer Science, Data Science, Mathematics, Finance, or related field.
• Minimum 6 years of experience in data analytics, risk management, or financial services.
• Hands-on experience with large language models and/or generative AI, including prompt engineering.
• Strong programming skills, with proven experience in Python.
• Experience with API integration (REST, SOAP, etc.) for data sourcing and processing.
• Background in process engineering and automation within financial services or risk management.
• Excellent problem-solving skills and ability to think outside the box.
• Strong communication and collaboration skills, with experience working across teams.
• Ability to document methodologies, code, and processes for transparency.
• Proven track record of delivering production-quality solutions.
• Experience in designing and implementing controls for automated processes.

• Prior experience with Snowflake or Databricks.
• Familiarity with liquidity risk concepts and regulatory requirements.
• Experience in developing and deploying data-driven models for risk management.
• Knowledge of asset and liability management, funding, and capital measurement processes.
• Experience in monitoring and reporting on liquidity positions and stress tests.
• Ability to independently review and assess risk management processes.
• Demonstrated ability to drive innovation and challenge the status quo.