Vice President, Data Scientist - Credit Risk, Risk Insights - Chase 360

About the role

Shape how JPMorganChase understands and manages consumer and small business credit risk at scale. In this role, you'll turn rich payment and customer data into insights that directly influence lending strategy and risk decisions. You'll partner with senior Risk leaders to answer high-impact questions, quantify tradeoffs, and monitor emerging risks. You'll also help modernize the analytics lifecycle by identifying where GenAI can deliver step-change improvements.

Responsibilities

• Utilize skills in data analysis, modeling, data engineering, and project management to initiate, develop, and complete advanced analytics projects.
• Perform credit-focused analytics to identify, quantify, and monitor risks in consumers and small businesses, leveraging diverse, large internal data sources.
• Translate complex data into clear, actionable insights that inform strategic decisions.
• Conduct independent research on emerging risks relevant to consumers and small businesses, proactively addressing new challenges and opportunities.
• Deliver executive-ready narratives—develop and communicate compelling insights, recommendations, and tradeoffs to senior leaders.
• Drive execution in a fast-paced environment, prioritizing across multiple initiatives, aligning stakeholders, and ensuring delivery against roadmap milestones and business outcomes.
• Embrace GenAI-enabled innovation across the data science lifecycle, and proactively identify where GenAI can create step-changes to existing processes and risk monitoring.
• Stay up to date on industry trends, macroeconomic developments, technological advances, and best practices in risk analytics.

Required Qualifications, Capabilities, and Skills

• Advanced degree in statistics, econometrics, or a related quantitative field, with minimum 5+ years of risk management or quantitative experience; alternatively, BS degree with a minimum of 7 years relevant experience.
• Deep expertise of the Consumer Financial Services industry.
• Demonstrated strategic and commercial mindset—ability to frame ambiguous problems, define clear success metrics, prioritize high-ROI work.
• Deep expertise in Python and SQL.
• Demonstrated analytical and problem-solving skills across conceptualization and execution of analytics oriented projects.
• Ability to synthesize diverse information and develop actionable recommendation.
• Ability to manage and prioritize competing activities and achieve tight timelines on complex deliverables.
• Ability to communicate complex findings clearly in both written format and verbally to technical and non-technical audiences.