Marketing Analytics Data Scientist Vice President

JP Morgan Chase; New York (NY); On-site; USD 250,000 - 360,000; Full time

Job summary

JPMorganChase is seeking a VP of Marketing Analytics Data Science to shape the analytics and AI roadmap for marketing initiatives. You will partner across marketing, product, data, technology, risk, legal, and compliance to deliver scalable, well-governed solutions that drive measurable outcomes.

You will own end-to-end delivery of analytics product roadmaps, shape high-impact use cases, and lead teams through prototyping to production while ensuring governance and risk controls align with firm

Qualifications

• 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.

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

Skills

Data science

Machine learning

Applied AI

Generative AI

Technical leadership

Communication

Marketing analytics

Software engineering concepts

Coaching & mentoring

Job description

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