Data Science Vice President - Card Data Analytics

You can help shape how data and AI drive decisions across our Credit Card business. You will work on high-impact problems end-to-end—translating business questions into analytical approaches, building models and solutions, and communicating insights that influence strategy and outcomes. Join a collaborative team where your work can directly improve customer and business experiences through responsible, scalable analytics. As a Data Science Vice President at JPMorganChase within the Card Data & Analytics team, you will develop analytics and AI/ML solutions that support strategic initiatives and measurable business impact. You will partner across the Card organization to define problems, scope solutions, and deliver high-quality analytical products. You will combine consulting, data science, and programming to drive data science and analytics strategies and deliver actionable insights. Job responsibilities Leverage experience and analytical skills to uncover novel use cases of Big Data analytics, including opportunities to responsibly apply foundation models and Generative AI Drive data science and analytics strategies, including recommendations on analytical products and standards Help partners define business problems and scope analytical solutions Build an understanding of problem domains and available data assets Research, design, implement, and evaluate analytical approaches and models, including Generative AI-based methods Perform exploratory statistics and data mining tasks on diverse datasets Communicate findings and obstacles to stakeholders to drive delivery to market Develop subject matter expertise in financial and operational domains Code solutions using strong programming skills Collaborate across teams to deliver the best solutions for clients Required qualifications, capabilities and skills Formal training or certification on software engineering concepts and 5+ years applied experience Bachelor's degree in a relevant quantitative field and 5+ years of data analytics experience, or advanced degree and 2+ years of experience Exceptional analytical, quantitative, problem-solving, and communication skills Intellectual curiosity for solving business problems Leadership and collaboration skills Knowledge of statistical software (for example, Python, R, SAS) and data querying languages (for example, SQL) Familiarity with Generative AI and prompt engineering basics (prompt design, evaluation, guardrails) Experience with modern analytics tools (for example, SAS, SQL, Hive, Hadoop, Spark, Python, Tableau, Alteryx) Ability to convey complex information to technical and non-technical audiences Preferred qualifications, capabilities and skills Experience with large language model-enabled applications such as retrieval-augmented generation, classification or extraction from unstructured text, or agent-like workflows; exposure to evaluation methods for quality, cost, and latency Understanding of key drivers within the credit card profit and loss statement Financial services background Master of Science degree or equivalent