Data Scientist Lead-Vice President

JPMorgan Chase & Co.•Columbus, OH

About The Position

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 a Data Scientist Lead on the Business Banking Lending Product Analytics team, 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.

Requirements

Bachelor’s degree in a quantitative field (e.g., Computer Science, Engineering, Statistics, Economics, or related discipline) and 5+ years of experience in advanced analytics roles.
Strong skills in SQL and modern analytics programming (e.g., Python/R) for data querying, transformation, analysis, and validation.
Proficiency in statistical analysis and product/customer analytics methods (e.g., hypothesis testing, predictive modeling, experimentation/measurement design).
Ability to translate ambiguous business questions into structured analytical approaches and actionable recommendations, with clear, executive-ready storytelling.
Effective working cross-functionally in a dynamic product environment, aligning stakeholders and driving decisions.
Competent using AI tools to accelerate insight generation and improve solution quality, applying them responsibly in a regulated environment.
Hands-on experience across data platforms (on-prem and cloud), such as Teradata/Oracle and AWS/Snowflake.

Nice To Haves

Familiarity with Business Banking lending products and processes is a plus.
Experience with experimentation, forecasting, segmentation, or predictive modeling in a product setting.
Experience working in a regulated environment with risk and controls expectations.

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).