Mid-Level
Join a team where your analysis directly influences how Chase invests in consumer banking growth. You will help measure marketing effectiveness, turn test learnings into strategy, and improve how we optimize marketing spend through a robust present value framework—while learning alongside a collaborative, inclusive group of data professionals.
As a Marketing Analytics Data Scientist at JPMorganChase within Consumer and Community Banking Data and Analytics, you will evaluate customer acquisition quality for deposit marketing initiatives, inform campaign strategy through rigorous experimentation, and improve investment decisions using discounted cash flow and customer lifetime value frameworks. You will develop, maintain, and enhance customer lifetime value and ad hoc estimates, and you will partner closely with stakeholders to translate analytical results into clear business recommendations that improve customer and business outcomes.
Job responsibilities
Develop and maintain customer lifetime value and discounted cash flow calculation frameworks to evaluate customer acquisition segment performance
Analyze deposit marketing initiatives to deliver campaign insights, recommendations, and strategic guidance
Design, execute, and evaluate experiments (including A/B and incrementality testing) to quantify impact and inform decisions
Support return-on-investment analyses and marketing investment portfolio optimization
Partner with finance on budgeting, forecasting, and cost-benefit evaluations tied to marketing investments
Collaborate cross-functionally with marketing analytics, test design, strategy, and finance partners to deliver outcomes in an inclusive, high-performing environment
Interpret and present findings to senior leaders with clear storytelling, implications, and recommended actions
Improve analytical workflows, documentation, and repeatable measurement approaches to enable scalable decision-making
Required qualifications, capabilities and skills
Bachelor’s and Master’s degree in a quantitative discipline (such as data science, analytics, mathematics, statistics, physics, engineering, economics, or finance)
3+ years of experience applying statistical methods to real-world business problems
3+ years of experience using SQL for data analysis
3+ years of experience using R for analytics and modeling
Experience supporting finance workstreams, including budgeting, forecasting, and return on investment or cost-benefit evaluations
Hands-on experience with A/B testing and incrementality testing, including experimental design, statistical significance evaluation, and translating results into business recommendations
Experience using AI-assisted development tools to accelerate analysis and code development
Experience with data visualization for analysis and executive-ready presentations
Strong written, verbal, and presentation skills, with the ability to communicate effectively across stakeholder groups and levels
Preferred qualifications, capabilities and skills
3+ years of applied experience using Python
Experience in marketing analytics, including customer acquisition and campaign measurement
Experience building data visualizations for analysis and presentations, including Tableau
Demonstrated ability to solve unstructured problems independently while maintaining strong stakeholder alignment
Strong strategic, organizational, and relationship-building skills to prioritize multiple initiatives and deliver on time
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