
at J.P. Morgan
Bulge Bracket Investment BanksPosted 4 days ago
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**Data Scientist Executive Director – Card Data & Analytics, Customer & Strategic Analytics, JPMorgan Chase:** - Lead analytics team for Card business, driving strategic insights & innovation via AI, machine learning, and advanced analytics. - Develop team strategy, build capability, and influence senior stakeholders by transforming complex data into clear, actionable business recommendations. - Collaborate cross-functionally to deliver end-to-end AI solutions, staying current with emerging techniques and ensuring solutions are scalable, responsible, and business-aligned. - Lead customer experience and benefits analytics initiatives, supporting product strategy, customer engagement, and portfolio performance. - Key skills: 10+ years in analytics, senior leadership, data science experience, technicalcurrency in Python/R, and proficiency with modern data platforms like Snowflake or Databricks. - Manage and mentor multi-layered team, fostering a high-performance, inclusive culture that stimulates professional growth and champions innovation.
- Compensation
- Not specified USD
- City
- Wilmington
- Country
- United States
Currency: $ (USD)
Full Job Description
Location: Wilmington, DE, United States
Join JPMorganChases 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 executionrequiring equal parts technical depth, strategic vision, and people leadership.
As a Data Scientist Director at JPMorganChase 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
- Masters 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 business domains, balancing near-term delivery with longer-term capability building
- Exceptional stakeholder management and communication skills, with a track record of influencing senior leaders and cross-functional partners
- Proficiency in Python and/or R, and experience with modern data platforms such as Snowflake or Databricks
- Strong project and program management skills, including the ability to define success metrics, manage risks, and drive execution across complex initiatives
Preferred qualifications, capabilities, and skills
- Experience in Card, consumer lending, or payments analytics, including familiarity with installment products, credit risk, or customer lifecycle management
- 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 using alternative data, market data, or external benchmarking
- 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




