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$142,300–$201,250.
Based on 240 similar postings.
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About JPMorgan Chase
JPMorgan Chase & Co. is a global financial services firm and one of the largest banks in the world, offering investment banking, commercial banking, asset management, and consumer financial services.
JPMorgan Chase currently has
1243 open roles
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As a Data Scientist Lead - Business Banking Lending - Vice President, you will join the team to shape the future of small business lending by partnering with Lending Strategy and Product leaders. You will act as a trusted analytics partner, framing high-impact business questions, building and validating datasets, and translating complex findings into actionable recommendations for senior stakeholders. Your daily work involves developing end-to-end analyses, establishing repeatable KPI and reporting frameworks with strong documentation, and identifying opportunities for automation and AI-assisted approaches. You must utilize SQL, Python, or R for data querying and transformation while applying statistical analysis methods like hypothesis testing and predictive modeling. This role focuses on performance insights across the lending lifecycle, deepening the understanding of customer behavior and supporting the evolution of lending products.
Design and deliver analytics to provide senior leaders with clear, actionable insights for lending products.
Own the end-to-end analysis process from initial problem framing and data sourcing to modeling and stakeholder review.
Translate complex technical findings into non-technical summaries and strategic recommendations for executive leadership.
Define and maintain KPI logic and documentation to ensure consistent measurement and auditability.
Build scalable analytical solutions and automated workflows to monitor performance and improve customer experience.
Identify growth opportunities by analyzing customer behavior and performance across the lending lifecycle.
Develop and validate datasets to support benchmarking, peer comparisons, and deep-dive analyses.
What we're looking for
Bachelor’s degree in a quantitative field such as Computer Science, Engineering, Statistics, Economics, or a related discipline.
5+ years of experience in advanced analytics roles.
Strong skills in SQL and modern analytics programming languages like Python or R.
Proficiency in statistical analysis and product/customer analytics methods including hypothesis testing and predictive modeling.
Ability to translate ambiguous business questions into structured analytical approaches and actionable recommendations with executive-ready storytelling.
Experience working cross-functionally in a dynamic product environment to align stakeholders and drive decisions.
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