Vice President Digital Marketing Analytics - Card Data Analytics

Posted today

jpmorgan chaseWilmington (NC)

Data Scientists Commercial Banking

SENIORITY

Manager

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About the role

You will help shape digital marketing strategy through rigorous analysis, experimentation, and clear storytelling that drives business outcomes. You will work with partners across Marketing, Finance, Product, and Technology to turn complex questions into measurable actions. You will grow and lead a high-performing analytics team, building scalable, reliable ways of working that improve how marketing decisions are made. As a Vice President, Digital Marketing Analytics at JPMorganChase within the Digital Marketing Analytics team, you will lead quantitative research and experimentation to optimize marketing performance and customer experiences. You will translate customer behavior and campaign performance into insights that leaders can act on, and you will build team capability through coaching, hiring, and a culture of scientific rigor and responsible use of advanced analytics. You will take a pragmatic approach to generative AI and large language models (LLMs) as complementary tools, while relying on classical statistical and causal methods for core measurement and optimization workstreams.

Job responsibilities:

Deliver effective quantitative problem solving and analytical research to support key digital marketing initiatives
Apply deep business understanding and advanced analytical techniques to drive research, experimentation, and measurable outcomes
Lead, mentor, hire, and develop a high-performing analytics team; promote scientific rigor, ethical AI, and continuous learning
Maintain a pragmatic approach to generative AI and large language models (LLMs) as complementary tools, prioritizing classical statistical methods for core measurement and optimization work
Partner with cross-functional teams (for example, Marketing and Finance) to drive insights into action and deliver business impact
Design and implement scalable, reliable analytics processes to optimize business outcomes
Conduct extensive analysis of marketing performance, measurement configuration and settings, and customer behavior to improve channel strategies and optimization using advanced quantitative methods
Own and support strategic measurement initiatives, including effectiveness evaluation and profit and loss analysis; quantify statistical and practical significance
Solve unstructured business problems and develop deep-dive analyses of customer behavior using multiple analytics and statistical techniques
Conduct hypothesis testing and advanced experimental design (A/B and multivariate tests) to measure the impact and effectiveness of marketing strategies
Required qualifications, capabilities and skills
Graduate or post-graduate degree in a quantitative discipline (for example, Computer Science, Statistics, Mathematics, Finance, Economics, Data Analytics, or Machine Learning)5+ years of hands‐on analytics experience in banking strategic analytics
Hands‐on proficiency with Python and SQL; experience with visualization tools (for example, Tableau) and analytics tools (for example, Alteryx)
Experience with Adobe Analytics (implementation, reporting, and insight generation)
Strong statistical or econometric foundation with hands‐on experimentation and measurement experience, including A/B testing, causal inference, and experimentation frameworks
Strong advanced analytics skills using SAS, Python, or RExcellent communication skills with the ability to translate complex models into clear explanations and reason codes, influencing cross‐functional stakeholders and senior leadership
Exposure to enterprise AI enablement, LLM‐assisted workflows, or analytics transformation programs
Ability to evaluate opportunities to apply AI, generative AI, and intelligent automation to improve investigative analysis, documentation, operating procedures, knowledge retrieval, issue summarization, and workflow efficiency
Familiarity with supervised learning, anomaly detection, semi‐supervised learning, clustering, feature stores, calibration and threshold optimization, and imbalanced learning
Preferred qualifications, capabilities and skills
Proficiency in big data extract, transform, and load processes across structured and unstructured data sources
Professional experience with AWS, Spark or EMR, and Snowflake
Experience with Confluence and generative AI tools (for example, ChatGPT), subject to firm‐approved usage
People leadership experience, including recruiting, coaching, performance management, and fostering an inclusive, high‐accountability culture
Strong understanding of IT processes and databases, with the ability to work directly with data owners and custodians

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