Vice President, Data Scientist Lead - Consumer Bank Marketing Analytics
JPMorgan Chase
- Location
- OH, United States
- Work model
- On-Site
- Level
- Staff
- H-1B history
- 1,524 approvals (FY2023)
- Posted
- 19h ago
Skills
About this role
Join Consumer Bank Marketing Analytics to transform data into insight and improve how customers discover, open, and use our products. In this role, you will lead analytics for the digital account opening experience and partner across Product, Technology, Marketing, Customer Experience, and Risk and Compliance to shape strategy, measurement, and prioritization. You will turn complex analysis into clear, actionable recommendations for senior stakeholders and help teams make faster, better decisions.
Job summary
As a Vice President, Data Scientist Lead in Consumer Bank Marketing Analytics , you will set the analytics direction for our digital account opening journey and define how we measure success. You will evaluate experiments, strengthen measurement frameworks, and improve dashboards to drive account production and customer experience outcomes. You will communicate insights with clarity and influence, helping cross-functional teams prioritize the changes that matter most. You will combine analytical rigor with strong storytelling and data visualization to connect performance trends to business actions. You will also apply modern automation and artificial intelligence tools to streamline delivery, improve consistency, and accelerate insights.
Job responsibilities
Lead analytics strategy, planning, and execution for the digital account opening experience, translating business questions into hypotheses, measurement plans, and decision-ready insights Monitor platform health and performance to detect anomalies, then partner with Product and Technology to diagnose root causes and reduce impact to customers and business results Measure funnel performance and segment and cohort engagement to identify abandonment points and friction, and partner across teams to improve completion rates Deliver actionable analytics for product and feature launches and journey optimization, quantifying impact on account production and quality over time Build and continuously improve business intelligence and measurement frameworks by defining and governing key performance indicators, standardizing metric definitions, and enhancing dashboard reliability and usability Define success metrics, guardrails, and data requirements to enable consistent reporting and faster decision-making Run experimentation analytics by sourcing data, sizing tests, analyzing results, and communicating recommendations to cross-functional partners and senior leaders Drive advanced analytics initiatives to deepen customer and journey insights and unlock new optimization opportunities Apply automation and artificial intelligence tools to streamline analyses, reduce cycle times, and accelerate insights Mentor and develop junior data scientists, serving as a subject matter expert for digital account opening experiences and measurement Maintain strong controls and documentation practices to support accurate, timely, and well-governed results Required qualifications, capabilities, and skills Master’s degree in a quantitative discipline (for example: data science, analytics, mathematics, statistics, engineering, economics, or finance) or equivalent directly applicable experience At least five years applying statistical methods to real-world problems (marketing analytics experience is a plus) At least five years of experience in analytics or data science supporting customer journeys, digital products, or operational workflows Experience using Adobe Analytics, Tableau, and Alteryx (or comparable tools) to define key performance indicators and build measurement frameworks, including guardrails and data quality checks Experience sizing, running, and evaluating A/B experiments and clearly communicating results to business and technical audiences Comfort using artificial intelligence tools (for example: GitHub Copilot, Claude Code, or Cortex) to accelerate analysis, pressure-test hypotheses, and prototype approaches Ability to independently troubleshoot and resolve technical, data, and