JPMorgan Chase & Co., one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world’s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.

As an Analytics Solutions Associate in JPMorgan Chase, you will monitor AI/ML models: track KPIs, triage alerts, improve automation, ensure compliance, and report insights to leaders.

Job Responsibilities:

• Model Monitoring: Do periodical monitoring of MLCOE’s AI/ML models, tracking key performance indicators (KPIs). Generate deep insights through the analysis of data and understanding of business processes and turn them into actionable recommendations.
• Alert Management: Investigate and triage alerts related to model performance, data anomalies, or system failures, escalating as appropriate.
• Continuous Improvement: Identify opportunities to enhance monitoring frameworks, automate processes, and improve operational efficiency.
• Stakeholder Collaboration: Collaborate with others in the organization to develop new ideas and brainstorm potential solutions.
• Reporting & Documentation: Prepare regular reports on model health, incidents, and remediation actions. Maintain up-to-date documentation of monitoring processes and findings.
• Leadership Communication: Develop presentations to summarize and communicate key messages to senior management and colleagues.
• Risk & Compliance: Ensure monitoring activities comply with regulatory requirements and internal model risk management policies.
• Change Management: Support the deployment of model updates, including validation, testing, and post-deployment monitoring.
• Operational Support: Support MLCOE’s SOPs Management function as and when required.

Required qualifications, capabilities, and skills

• Bachelor’s / master’s degree in computer science, engineering, data science, or business.

• Minimum 4 years of experience in model monitoring, analytics, operations, or a related role.

• Understanding of AI/ML concepts and model lifecycle management.

• Experience with data analysis tools (e.g., Python, SQL, Excel).

• Strong data analysis and troubleshooting abilities.

• Excellent communication and documentation skills.

• Detail-oriented with strong organizational abilities.

• Ability to work collaboratively in a cross-functional, fast-paced environment.

• Familiarity with model risk management frameworks and regulatory guidelines.

• Exposure to cloud platforms (e.g., AWS, Azure, GCP) and MLOps practices.