Data Scientist Executive Director – Card Data & Analytics, Customer & Strategic Analytics

JPMorgan Chase JPMorgan Chase · Banking · Wilmington, DE +1 · Consumer & Community Banking

Executive Director Data Scientist at JPMorgan Chase leading a team focused on AI, machine learning, and advanced analytics for the Card business. The role involves defining AI strategy, delivering AI/ML solutions from ideation to production, supporting customer experience, driving experimentation, and leading a team of analytics professionals. Requires strong leadership, technical depth, and business acumen, with a focus on driving measurable business impact and competitive advantage.

What you'd actually do

  1. Define and drive the AI strategy for Card Data & Analytics, identifying high-value opportunities for generative AI, agentic AI, and analytics innovation to create competitive advantage
  2. Partner with Data, Product, and Technology to deliver AI and machine learning solutions from ideation and prototyping through production deployment, ensuring solutions are scalable, responsible, and aligned to business needs
  3. Stay current on emerging AI and machine learning techniques and translate new capabilities into practical applications for the Card business
  4. Lead analytics supporting customer experience and benefits, delivering insights that inform customer engagement, product design, portfolio performance, and pricing and targeting strategies
  5. Partner with Product, Risk, and Finance stakeholders to define analytical priorities, interpret results, and drive data-informed decisions

Skills

Required

  • Master’s or PhD in a quantitative field
  • 10+ years of analytics experience
  • Proven senior leadership experience managing and developing multi-disciplinary analytics teams
  • Deep expertise in data science and analytics
  • hands-on experience with predictive modeling, statistical analysis, segmentation, and experimentation
  • Demonstrated ability to deliver AI, machine learning, and analytics solutions that drive measurable business outcomes
  • Strong business acumen
  • Experience leading analytics across multiple concurrent business domains
  • Exceptional stakeholder management and communication skills
  • Proficiency in Python and/or R
  • experience with modern data platforms such as Snowflake or Databricks
  • Strong project and program management skills

Nice to have

  • Experience in Card, consumer lending, or payments analytics
  • Hands-on experience with generative AI solutions, including large language models, retrieval-augmented generation, and agentic AI frameworks
  • Experience building or leading competitive intelligence functions
  • Experience with causal inference, A/B testing, and experimentation frameworks at scale
  • Familiarity with responsible AI principles, model governance, and regulatory considerations in financial services
  • Experience enabling analytics adoption through change management, self-service tooling, or organizational enablement
  • Familiarity with Agile delivery methods and modern product practices

What the JD emphasized

  • AI strategy
  • generative AI
  • agentic AI
  • AI and machine learning solutions
  • emerging AI and machine learning techniques
  • responsible AI principles
  • regulatory considerations in financial services

Other signals

  • leading end-to-end delivery of AI and analytics solutions
  • define and drive the AI strategy
  • partner with Data, Product, and Technology to deliver AI and machine learning solutions from ideation and prototyping through production deployment
  • stay current on emerging AI and machine learning techniques and translate new capabilities into practical applications
  • lead analytics supporting customer experience and benefits
  • drive measurement frameworks, experimentation (including A/B testing and causal inference), and personalization strategies
  • translate customer data into actionable insights
  • build and lead competitive intelligence analytics capabilities
  • deliver forward-looking analyses that inform strategic planning and product roadmap decisions
  • lead, mentor, and develop a multi-layered team of analytics leaders, data scientists, and analysts
  • attract and retain top analytics talent
  • champion a culture of innovation, intellectual rigor, and collaborative problem-solving