Quant Analytics Associate Senior - Consumer Bank Marketing Analytics

JPMorgan Chase & Co.•Columbus, OH

About The Position

Join a high-impact team turning data into decisions that improve how customers discover, open, and use our products. You’ll collaborate across product, technology, marketing, customer experience, and risk to shape strategy and accelerate outcomes. This role offers growth, mobility, and the chance to influence firmwide priorities through rigorous analytics and clear storytelling. Bring your curiosity and craft—your work will be seen, used, and valued. As a Senior Associate, Quantitative Analytics in Consumer Bank Marketing Analytics, you transform complex data into practical guidance that improves the digital account opening experience. You will define success metrics, align partners on priorities, and ensure decisions are grounded in facts. You elevate business intelligence quality, uncover opportunities to optimize account opening journeys, and increase conversion. You communicate insights clearly to stakeholders at all levels, enabling faster, more confident decisions. You will work in a cross-functional squad to monitor platform health, understand customer behavior across segments and cohorts, and translate findings into actionable recommendations. You will drive measurement frameworks for new features and launches, support rapid experimentation, and help shape the roadmap with credible evidence.

Requirements

Bachelor’s degree in Business Analytics, Data Science, Mathematics, Statistics, Management Information Systems, or a related field of study.
Minimum three years analyzing customer experiences and journeys.
Minimum three years of hands-on experience with SQL and Python.
Minimum three years of experience with Adobe Analytics, Tableau, and Alteryx.
Practical experience with behavioral and transactional analytics tools and techniques.
Experience working with business intelligence platforms to deliver dashboards.
Experience sizing and evaluating digital A/B experiments.
Demonstrated ability to define business KPIs and establish measurement frameworks.
Strong PowerPoint and slide-writing skills to deliver analytical insights.
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

Digital product, marketing, or analytics experience.
Experience in the financial services industry.
Knowledge and experience leveraging AI tools to improve efficiency and accelerate insights.
Data-driven and analytical mindset coupled with creative problem-solving.
Experience with customer journey analytics and marketing technology ecosystems.
Familiarity with experimentation platforms and feature-flag frameworks.

Responsibilities

Monitor digital account opening platform health, detect anomalies, and partner with product and technology to diagnose and resolve issues that mitigate customer and business impact.
Measure funnel performance end-to-end; analyze segments and cohorts, pinpoint abandonment and friction, and recommend changes that improve completion rates.
Define success metrics and robust measurement frameworks; align stakeholders on priorities and ensure decisions are data-driven.
Build interactive dashboards and executive-level reports on engagement and funnel health to enable quick, informed decisions and guide product and technology priorities.
Provide analytics to inform business and marketing strategies for new products and features; quantify opportunities, remove friction, and boost conversion with measurable outcomes.
Partner with Test Design to source data, size digital experiments, prioritize the experimentation roadmap, and analyze A/B test results; communicate implications to squad members and senior leadership.
Collaborate with Analytics and Marketing to craft integrated narratives on performance drivers and customer behavior trends.
Apply AI tools and automation to streamline analyses, reduce cycle times, and accelerate insights.
Uphold data quality and governance standards; validate inputs, document methods, and ensure reproducible analyses.
Mentor peers on best practices in measurement, visualization, and data storytelling.