Marketing Analytics Data Scientist Vice President

JPMorgan Chase & Co. • New York, NY

2d • $147,250 - $215,000

About The Position

As a Vice President, Marketing Analytics Data Scientist within JPMorganChase’s Consumer and Community Banking division, you will lead the analytics and artificial intelligence roadmap for marketing analytics and decisioning. You will partner with marketing, product, data, technology, risk, legal, and compliance teams to deliver scalable, well-governed, measurable solutions.

The role translates business opportunities and marketing needs into production analytics and AI solutions. It covers solution design and technical direction for machine learning, generative AI—including retrieval-augmented generation and fine-tuning where appropriate—and agent-based workflows. You will guide delivery from prototyping through production deployment, monitoring, and optimization, while establishing practices for reproducibility, documentation, code quality, and model governance.

You will develop models and measurement frameworks that support marketing decisions and connect solutions to outcomes such as incrementality, conversion, retention, engagement, and operational efficiency. Solutions must meet firm standards for model risk management, privacy, security, fairness, explainability, and auditability.

Requirements

• Formal training or certification in software engineering concepts and at least 5 years of applied experience.
• At least 2 years of demonstrated coaching and mentoring experience.
• At least 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 AI solutions, including orchestration concepts for agent-based workflows.
• Proven ability to lead technical teams and deliver in complex stakeholder environments.
• Strong written and verbal communication skills, including the ability to influence senior leaders through clear narratives and measurable results.
• Marketing analytics experience applying analytics to targeting, lifecycle programs, or performance measurement.

Nice To Haves

• Experience in financial services or another highly regulated environment, with demonstrated control discipline.
• Deep understanding of marketing measurement and experimentation, including A/B testing, incrementality, and causal inference.
• Experience integrating analytics and AI into marketing execution and decisioning platforms, such as audience selection, journey orchestration, and outbound channels.
• Experience building attribution or marketing mix measurement support capabilities in partnership with measurement teams.

Responsibilities

• Own end-to-end delivery of the analytics and AI 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 with enterprise data and platform standards.
• Lead solution design and technical direction for machine learning, generative AI—including retrieval-augmented generation and fine-tuning when appropriate—and agent-based workflow patterns.
• Drive engineering and data science execution across the solution lifecycle, from prototyping through 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, including incrementality, conversion, retention, engagement, and operational efficiency.
• Ensure solutions meet firm standards for model risk management, data privacy, security, fairness testing, explainability, and auditability.

Benefits

• Competitive total rewards package, including base salary determined by role, experience, skill set, and location.
• Eligible roles may receive commission-based pay and/or discretionary incentive compensation in cash and/or forfeitable equity.
• Comprehensive health care coverage.
• On-site health and wellness centers.
• Retirement savings plan.
• Backup childcare.
• Tuition reimbursement.
• Mental health support.
• Financial coaching.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed