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

Job in Wilmington, New Castle County, Delaware, 19894, USA
Listing for: JPMorgan Chase & Co.
Full Time position
Listed on 2026-05-29
Job specializations:
  • IT/Tech
    Data Analyst, Data Science Manager
Salary/Wage Range or Industry Benchmark: 100000 - 125000 USD Yearly USD 100000.00 125000.00 YEAR
Job Description & How to Apply Below

Join JPMorgan

Chase’s Card business as a Data Scientist Director, leading the Card Data & Analytics Customer & Strategic Analytics team. You will lead a high-performing organization of analytics leaders, data scientists, and analysts to drive measurable business impact through AI, machine learning, and advanced analytics. This is a senior leadership role that sits at the intersection of innovation and execution—requiring equal parts technical depth, strategic vision, and people leadership.

As a Data Scientist Director at JPMorgan

Chase within the Card Data & Analytics Customer & Strategic Analytics team, you will lead end-to-end delivery of AI and analytics solutions that shape product strategy, customer experience, and competitive positioning. You will build and develop a diverse team of analytics professionals, set technical and analytical direction across multiple business domains, and translate complex insights into clear, actionable recommendations for senior stakeholders.

You will foster a culture of intellectual curiosity, inclusion, and continuous improvement while influencing roadmaps, shaping business decisions, and building organizational capability.

Job responsibilities
  • 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
  • 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
  • Stay current on emerging AI and machine learning techniques and translate new capabilities into practical applications for the Card business
  • Lead analytics supporting customer experience and benefits, delivering insights that inform customer engagement, product design, portfolio performance, and pricing and targeting strategies
  • Partner with Product, Risk, and Finance stakeholders to define analytical priorities, interpret results, and drive data-informed decisions
  • Drive measurement frameworks, experimentation (including A/B testing and causal inference), and personalization strategies that improve customer experience and benefits utilization
  • Translate customer data into actionable insights that inform marketing, product, and servicing strategies.

    Build and lead competitive intelligence analytics capabilities that monitor market trends, competitor positioning, and industry benchmarks within the Card space

  • Partner with external vendors and synthesize internal and external data sources to provide senior leaders a clear view of the competitive landscape
  • Deliver forward‑looking analyses that inform strategic planning and product roadmap decisions for the Card business
  • Lead, mentor, and develop a multi‑layered team of analytics leaders, data scientists, and analysts, fostering a high‑performance, inclusive, growth‑oriented culture.

    Set clear goals and performance expectations, provide ongoing coaching, and support career development across all levels of the team

  • Attract and retain top analytics talent through hiring, onboarding, and skills development programs.

    Champion a culture of innovation, intellectual rigor, and collaborative problem‑solving across the broader Card Data & Analytics organization.

Required qualifications, capabilities, and skills
  • Master’s or PhD in a quantitative field and 10+ years of analytics experience
  • Proven senior leadership experience managing and developing multi‑disciplinary analytics teams, including managers and individual contributors, in a large enterprise environment
  • Deep expertise in data science and analytics, including 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, ideally within financial services or consumer products
  • Strong business acumen with the ability to frame analytical problems in terms of business strategy and translate insights into executive‑level recommendations
  • Experience leading analytics across multiple concurrent…
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