Marketing Analytics Data Scientist Vice President

Bring your strategic thinking and deep analytics expertise to a role where your work shapes how we deliver more relevant, responsible, and measurable marketing. You will help translate business opportunities into scalable analytics and artificial intelligence solutions, partnering across teams to move ideas into production and drive real outcomes.
As a Vice President, Marketing Analytics Data Science at JPMorganChase within Consumer and Community Banking, you will lead the analytics and artificial intelligence roadmap for marketing analytics and decisioning. You will partner closely with marketing, product, data, technology, risk, legal, and compliance to deliver solutions that are scalable, well-governed, and measurable from end to end.
Job responsibilities
Own the end-to-end delivery of the analytics and artificial intelligence product roadmap for marketing analytics, including prioritization, sequencing, resourcing, and dependency management
Identify and shape high-impact use cases such as next best action, audience selection, lifecycle optimization, content intelligence, and measurement automation
Translate marketing and analytics needs into scalable technical solutions aligned to enterprise data and platform standards
Lead solution design and technical direction for machine learning, generative artificial intelligence (including retrieval-augmented generation and fine-tuning when appropriate), and agent-based workflow patterns
Drive engineering and data science execution across the full solution lifecycle, from prototyping to production deployment, monitoring, and optimization
Establish team best practices for reproducibility, documentation, code quality, and model governance
Develop and operationalize models for propensity, churn and retention, uplift and causal impact, segmentation, channel optimization, and experimentation
Build measurement frameworks that connect solutions to marketing outcomes such as incrementality, conversion, retention, engagement, and operational efficiency
Ensure solutions meet firm standards for model risk management, data privacy, security, fairness testing, explainability, and auditability
Required qualifications, capabilities and skills
Formal training or certification on software engineering concepts and 5+ years applied experience
2+ years of demonstrated coaching and mentoring experience
5+ years of experience in data science, machine learning, or applied artificial intelligence, with a track record of delivering production solutions
Hands-on experience designing machine learning and generative artificial intelligence solutions, including orchestration concepts for agent-based workflows
Proven ability to lead technical teams and deliver across complex stakeholder environments
Strong written and verbal communication skills with the ability to influence senior leaders using clear narratives and measurable results
Marketing analytics experience, including applying analytics to targeting, lifecycle programs, or performance measurement
Preferred qualifications, capabilities and skills
Experience in financial services or other highly regulated environments with demonstrated control discipline
Deep understanding of marketing measurement and experimentation, including A/B testing, incrementality, and causal inference
Experience integrating analytics and artificial intelligence into marketing execution and decisioning platforms (for example, audience selection, journey orchestration, and outbound channels)
Experience building attribution or marketing mix measurement support capabilities in partnership with measurement teams

Skills
Machine Learning, Artificial Intelligence, Prototyping, Risk Management, Documentation