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Vice President, Digital Marketing Analytics

Job in Wilmington, New Castle County, Delaware, 19894, USA
Listing for: JPMorganChase
Full Time position
Listed on 2026-08-25
Job specializations:
  • IT/Tech
    Data Analyst, Data Scientist, Data Science Manager, AI Engineer (Applied/Software)
Salary/Wage Range or Industry Benchmark: 180000 - 260000 USD Yearly USD 180000.00 260000.00 YEAR
Job Description & How to Apply Below

Job Description

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.

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 JPMorgan

Chase 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 work streams.

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 R
  • Excellent 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,…
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