Vice President, Digital Marketing Analytics

Vice President, Digital Marketing AnalyticsYou 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 responsibilitiesDeliver effective quantitative problem solving and analytical research to support key digital marketing initiativesApply deep business understanding and advanced analytical techniques to drive research, experimentation, and measurable outcomesLead, mentor, hire, and develop a high-performing analytics team; promote scientific rigor, ethical AI, and continuous learningMaintain a pragmatic approach to generative AI and large language models (LLMs) as complementary tools, prioritizing classical statistical methods for core measurement and optimization workPartner with cross-functional teams (for example, Marketing and Finance) to drive insights into action and deliver business impactDesign and implement scalable, reliable analytics processes to optimize business outcomesConduct extensive analysis of marketing performance, measurement configuration and settings, and customer behavior to improve channel strategies and optimization using advanced quantitative methodsOwn and support strategic measurement initiatives, including effectiveness evaluation and profit and loss analysis; quantify statistical and practical significanceSolve unstructured business problems and develop deep-dive analyses of customer behavior using multiple analytics and statistical techniquesConduct hypothesis testing and advanced experimental design (A/B and multivariate tests) to measure the impact and effectiveness of marketing strategiesRequired qualifications, capabilities and skillsGraduate 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 analyticsHands-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 frameworksStrong 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 leadershipExposure to enterprise AI enablement, LLM-assisted workflows, or analytics transformation programsAbility to evaluate opportunities to apply AI, generative AI, and intelligent automation to improve investigative analysis, documentation, operating procedures, knowledge retrieval, issue summarization, and workflow efficiencyFamiliarity with supervised learning, anomaly detection, semi-supervised learning, clustering, feature stores, calibration and threshold optimization, and imbalanced learningPreferred qualifications, capabilities and skillsProficiency in big data extract, transform, and load processes across structured and unstructured data sourcesProfessional experience with AWS, Spark or EMR, and SnowflakeExperience with Confluence and generative AI tools (for example, ChatGPT), subject to firm-approved usagePeople leadership experience, including recruiting, coaching, performance management, and fostering an inclusive, high-accountability cultureStrong understanding of IT processes and databases, with the ability to work directly with data owners and custodians