VP Data Scientist, Credit Risk Analytics & Strategy

Testing Site - JPMC; Columbus (OH); On-site; USD 180,000 - 280,000; Full time

Job summary

JPMorganChase in Columbus, OH seeks a Vice President Data Scientist to lead end-to-end analytical work powering credit strategy for consumer and small business lending. You will own data engineering, feature development, modeling, interpretation, and executive storytelling to surface timely insights and dashboards for senior risk leaders.

The role requires strong Python and SQL, production-grade coding, and experience building credit models and risk dashboards.

Qualifications

• Advanced degree (MS preferred) in statistics, econometrics, or related quantitative field with minimum 7 years in risk management or quantitative roles; or BS with 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) and production-grade code practices.
• Advanced SQL skills with 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.

Responsibilities

• Generate timely insights on consumer and small-business health using cross-LOB data to identify, quantify, and monitor emerging credit risks.
• Inform and influence credit strategies across Card, Auto, Home Lending, and Business Banking with data-driven recommendations and scenario analysis.
• Engineer and maintain high-quality attributes/features to support credit models, segmentation, and policy execution.
• Design and execute advanced analytics (e.g., risk segmentation, early-warning signals, stress indicators) to track portfolio trends and headwinds.
• Build and automate dashboards and recurring reports that translate complex analytics into clear, actionable leadership narratives.
• Conduct independent research on macro, industry, and payment trends; connect external developments to portfolio risks and opportunities.
• Analyze peer publications and public data releases to produce differentiated viewpoints for CCB Risk leadership.
• Partner with data engineering, model, and product teams to operationalize insights and ensure scalability, resiliency, and governance.
• Manage cross-functional projects end-to-end, aligning stakeholders, defining milestones, and delivering on time in a fast-paced environment.
• Communicate findings to technical and non-technical audiences, using crisp narratives, visuals, and executive-ready materials.
• Champion best practices in code quality, reproducibility, and model/metric documentation to elevate team capabilities.

Skills

Python

SQL

Data wrangling

Credit risk analytics

Risk modeling

Dashboards

Executive storytelling

Cross-functional collaboration

Model governance

Cloud computing

Education

MS in statistics or quantitative field

BS with 8+ years experience in relevant field

Tools

Tableau

Power BI

Airflow

AWS

Spark

Job description

JPMorganChase in Columbus, OH seeks a Vice President Data Scientist to lead end-to-end analytical work powering credit strategy for consumer and small business lending. You will own data engineering, feature development, modeling, interpretation, and executive storytelling to surface timely insights and dashboards for senior risk leaders.

The role requires strong Python and SQL, production-grade coding, and experience building credit models and risk dashboards.