Data Scientist Lead - Business Banking Lending - Vice President

JP Morgan Chase; Columbus (OH); On-site; USD 180,000 - 260,000; Full time

Job summary

JP Morgan Chase is seeking a Data Scientist Lead - Business Banking Lending - Vice President to partner with stakeholders and design analytics that drive executive decisions. You will build KPI frameworks, perform deep-dive analyses, and translate complex data into actionable recommendations while upholding data quality and governance.

This role focuses on growth and performance insights across the lending lifecycle, with opportunities to apply AI methods to improve products and customer

Qualifications

• Bachelor’s degree in a quantitative field and 5+ years in advanced analytics.
• Strong SQL and modern analytics programming (Python/R) skills.
• Experience translating ambiguous business questions into structured analytics and executive-ready recommendations.
• Ability to work cross-functionally in a dynamic product environment.

Responsibilities

• Build relationships with Product Managers and partners.
• Own analyses and end-to-end reporting from framing to insights.
• Translate findings into clear summaries for senior stakeholders.
• Define KPI logic and maintain documentation for auditability.
• Identify opportunities to automate measurements and apply AI where appropriate.

Skills

SQL

Python/R

Statistical analysis

Cross-functional work

Education

Bachelor's degree in quantitative field

Job description

Bring your quantitative skills to help shape the future of small business lending. If you enjoy tackling ambiguous problems, building strong measurement frameworks, and using modern analytics and AI to create executive-ready insights, you’ll thrive in this role.

As aData Scientist Lead - Business Banking Lending - Vice President, you’ll partner closely with business stakeholders to design and deliver analytics that senior leaders can act on; turning complex data into clear, confident decisions.You’ll partner closely with Lending Strategy and Product leaders to build defensible metrics, run deep-dive analyses, and deliver benchmarking and reporting that leadership can act on.This role will require you to be strategy-oriented and focused on performance insights across the lending lifecycle.

You will operate as a trusted analytics partner—framing high-impact business questions, defining measurement approaches, building and validating datasets, and translating complex findings into clear, actionable recommendations. You will establish repeatable KPI and reporting frameworks (with strong documentation and controls), deliver benchmarking and peer comparisons where relevant, and help build scalable analytical solutions that improve how we monitor performance and support our customers and bankers.

Your work will drive meaningful business impact by deepening our understanding of customer behavior, identifying growth and experience opportunities, and supporting the ongoing evolution of our lending products—while maintaining strong data quality and governance.

Job Responsibilities

• Build strong relationships with Product Managers and functional partners (Operation, Risk, Controls, Finance, Tech).
• Own the development and execution of analyses and reporting from end to end (problem framing→ data sourcing→ analysis/modeling→ insights→ stakeholder review).
• Translate complex findings into clear, non-technical summaries and recommendations for senior stakeholders.
• Think from a business standpoint and connect the “why” to the data, assumptions, and trade-offs.
• Define and maintain KPI logic and documentation to support auditability and consistent measurement.
• Identify opportunities to improve measurement, automation, and analytical workflows (including AI-assisted approaches where appropriate).

Required Qualifications, Capabilities, and Skills

• Bachelor’s degree in a quantitative field (e.g., Computer Science, Engineering, Statistics, Economics, or related discipline) and5+ yearsof experience in advanced analytics roles.
• Strong skills inSQLand modern analytics programming (e.g.,Python/R) for data querying, transformation, analysis, and validation.
• Proficiency instatistical analysisand product/customer analytics methods (e.g., hypothesis testing, predictive modeling, experimentation/measurement design).
• Ability to translate ambiguous business questions into structured analytical approaches andactionable recommendations, with clear, executive-ready storytelling.
• Effective workingcross-functionallyin a dynamic product environment, aligning stakeholders and driving decisions.