Data Scientist Lead - Consumer Bank Marketing Analytics - VP

JPMorgan Chase & Co.•Columbus, OH

About The Position

Join Consumer Bank Marketing Analytics to transform data into insight and improve how customers discover, open, and use our products. As a Data Scientist Lead, you will lead cross-line of business analytics efforts that streamline referrals and modernize marketing offer discovery. You will partner across Product, Technology, Marketing, Customer Experience, and Risk/Compliance to shape strategy and drive business results. You will use advanced analytics and AI-enabled tooling to accelerate delivery, improve consistency, and raise the bar on measurement and decisioning. As a Data Scientist Lead in Consumer Bank Marketing Analytics, you will own the analytics strategy for marketing offer transformation initiatives that improve offer discovery, fulfillment, and referral experiences for customers and bankers. In a cross-functional quad, you will define success metrics and guardrails, size and evaluate experiments, and deliver dashboards and reporting that enable consistent, reliable decision-making. You will translate complex analyses into clear, decision-ready recommendations for senior stakeholders and align partners on the highest-impact work. You will maintain a rigorous controls environment and strong data quality practices while collaborating closely with Risk/Compliance. You will mentor junior data scientists and help build shared measurement standards across journeys and channels.

Requirements

Bachelor’s degree in Data Science, Statistics, Mathematics, Computer Science, Business Analytics, MIS, or a related field.
5+ years of experience in analytics/data science supporting customer journeys, digital products, or operational workflows.
5+ years of hands-on experience with SQL and Python.
5+ years of experience with Adobe Analytics, Tableau, and Alteryx (or comparable tools).
Proven experience defining KPIs and building measurement frameworks, including guardrails and data quality checks.
Demonstrated experience sizing and evaluating A/B experiments and communicating results to business and technical audiences.
Strong dashboarding/BI skills, including metric governance, performance optimization, and executive-ready reporting.
Strong slide-writing and storytelling skills to deliver clear narratives and recommendations.
Excellent communication, influence, and stakeholder management skills, with ability to lead through ambiguity and drive outcomes.
Strong communication skills to translate complex analyses into clear narratives for executive, business, and technical audiences.
Proven ability to take initiative, influence others, and achieve results.

Nice To Haves

Experience in financial services and/or other regulated environments.
Demonstrated experience using AI coding tools (for example, GitHub Copilot, Claude Code, Cortex) to improve productivity and accelerate insights.
Intellectually curious and eager to become a subject matter expert in your focus area.
Creative problem solver with strong analytical rigor.
Strong communicator who can build relationships with key stakeholders.

Responsibilities

Lead the analytics strategy, planning, and execution for marketing offer transformation by turning business problems into hypotheses, measurement plans, and decision-ready insights.
Shape the offer transformation roadmap by identifying capability gaps (data, platform, process, and experience), quantifying customer impact and business value, and aligning the quad on highest-impact workstreams.
Provide actionable analytics for referral capability enhancements and offer journey optimization, measuring impact on acquisition, activation, engagement, fulfillment, and quality outcomes.
Lead experimentation and test design by sourcing data, defining success and guardrail metrics, sizing A/B tests, analyzing results, and communicating recommendations to the quad and senior leadership.
Define and govern a cross-line of business measurement framework by establishing KPIs, standardizing metric definitions, and aligning success metrics and guardrails across channels and journeys.
Build and continuously improve dashboards and reporting to enable reliable decision-making, improving usability, timeliness, data quality controls, and self-service consumption.
Drive advanced analytics to identify journey friction, improve offer fulfillment, and increase customer engagement across digital and banker-assisted experiences.
Apply AI tools and automation to streamline analysis workflows, reduce cycle time, and accelerate insight delivery with consistent quality.
Provide leadership and mentorship to junior data scientists as a subject matter expert for offer fulfillment experiences and measurement practices.
Maintain a rigorous controls environment to ensure accurate, timely, and well-governed analyses, including documentation, data validation, and appropriate Risk/Compliance partnership.