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

JPMorgan Chase JPMorgan Chase · Banking · Columbus, OH +1 · Consumer & Community Banking

This role focuses on credit risk analytics within the fintech domain, leveraging advanced data science techniques and cross-line-of-business data to inform credit strategy, identify emerging risks, and build features for credit models. The primary output involves data engineering, feature development, and delivering analytical insights and dashboards to senior leadership.

What you'd actually do

  1. Generate timely insights on consumer and small‑business health using cross‑LOB data to identify, quantify, and monitor emerging credit risks.
  2. Inform and influence credit strategies across Card, Auto, Home Lending, and Business Banking with data‑driven recommendations and scenario analysis.
  3. Engineer and maintain high‑quality attributes/features to support credit models, segmentation, and policy execution.
  4. Design and execute advanced analytics (e.g., risk segmentation, early‑warning signals, stress indicators) to track portfolio trends and headwinds.
  5. Build and automate dashboards and recurring reports that translate complex analytics into clear, actionable leadership narratives.

Skills

Required

  • Advanced degree (MS preferred) in statistics, econometrics, or related quantitative field
  • minimum 7 years in risk management or quantitative roles
  • minimum 8 years relevant experience
  • Experience in consumer financial services with a focus on credit risk analytics and portfolio monitoring across the credit lifecycle
  • Strong Python proficiency (data wrangling, modeling, visualization, automation)
  • production-grade code practices
  • Advanced SQL skills
  • proven ability to query, transform, and QC large, complex datasets from multiple sources
  • Demonstrated ability to build, maintain, and validate attributes/features for credit models and strategy execution
  • Track record of delivering time‑critical analytical reports/dashboards to senior stakeholders with clear, actionable insights
  • Strong quantitative problem‑solving, hypothesis‑driven analysis, and experimental design skills
  • Excellent communication skills, translating technical analyses into concise recommendations for leadership
  • Self‑starter with ownership mindset
  • proven ability to drive ambiguous problems to scalable solutions under tight timelines
  • Familiarity with integrating external data/publications and macro trends into credit risk assessments
  • Project management experience leading cross‑functional initiatives from scoping through delivery and adoption

Nice to have

  • Experience with payments data, spend behaviors, and early‑warning indicators tied to consumer and small‑business health
  • Knowledge of credit risk modeling techniques and performance monitoring
  • Proficiency with data visualization/BI tools (e.g., Tableau, Power BI) for automated reporting
  • Familiarity with cloud data platforms and distributed computing (e.g., AWS, Spark) for large‑scale analytics
  • Experience partnering across business lines and risk functions to align strategies and implement analytics at scale
  • Strong sense of learning agility—comfort quickly adopting new tools, methods, and business concepts

What the JD emphasized

  • minimum 7 years in risk management or quantitative roles
  • minimum 8 years relevant experience
  • consumer financial services with a focus on credit risk analytics and portfolio monitoring
  • Strong Python proficiency
  • production-grade code practices
  • Advanced SQL skills
  • query, transform, and QC large, complex datasets
  • Track record of delivering time‑critical analytical reports/dashboards to senior stakeholders
  • clear, actionable insights
  • Self‑starter with ownership mindset
  • drive ambiguous problems to scalable solutions
  • tight timelines