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About JPMorgan Chase
JPMorgan Chase & Co. is a global financial services firm and one of the largest banks in the world, offering investment banking, commercial banking, asset management, and consumer financial services.
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1173 open roles
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As Vice President Digital Marketing Analytics - Card Data Analytics, you will join the Digital Marketing Analytics team to shape strategy through rigorous analysis, experimentation, and clear storytelling. You will lead a high-performing analytics team, managing hiring, coaching, and building scalable processes to improve marketing decision-making. Your daily work involves translating customer behavior and campaign performance into actionable insights for cross-functional partners in Finance, Product, and Technology. You will conduct advanced experimental designs like A/B and multivariate testing while utilizing classical statistical methods and causal inference for core measurement. The role requires proficiency in Python, SQL, SAS, R, Tableau, Alteryx, and Adobe Analytics. You will also navigate the integration of generative AI and LLMs into workflows. Key technical domains include supervised learning, anomaly detection, clustering, and big data processing using AWS, Spark, EMR, and Snowflake.
Lead, mentor, and hire a high-performing analytics team while promoting scientific rigor and ethical AI.
Conduct quantitative research and advanced experimentation to optimize marketing performance and customer experiences.
Translate complex customer behavior and campaign data into actionable insights for senior leadership.
Design and implement scalable, reliable analytics processes to improve how marketing decisions are made.
Execute A/B and multivariate testing to measure the impact of marketing strategies.
Manage strategic measurement initiatives including effectiveness evaluation and profit and loss analysis.
Integrate generative AI and LLMs as complementary tools while prioritizing classical statistical methods for core measurements.
Solve unstructured business problems by developing deep-dive analyses using various statistical techniques.
What we're looking for
Graduate or post-graduate degree in a quantitative discipline such as Computer Science, Statistics, Mathematics, Finance, Economics, Data Analytics, or Machine Learning.
5+ years of hands-on analytics experience in banking strategic analytics.
Proficiency with Python and SQL, along with experience using visualization tools like Tableau and analytics tools like Alteryx.
Experience with Adobe Analytics for implementation, reporting, and insight generation.
Strong statistical or econometric foundation including A/B testing, causal inference, and experimentation frameworks.
Advanced analytics skills using SAS, Python, or R.
Ability to translate complex models into clear explanations to influence cross-functional stakeholders and senior leadership.
Experience with big data ETL processes, AWS, Spark, Snowflake, and people leadership (preferred).
AI
ML
Generative AI
Agentic AI
Large Language Models
Retrieval-Augmented Generation
Python
R
Snowflake
Databricks
Causal Inference
A/B Testing
Experimentation
MLOps
Data Architecture
Agile
Analytics Strategy