Data & Marketing Systems Quant Analytics Manager-Vice President

JPMorgan Chase & Co.•Wilmington, DE

12d

About The Position

As a Quantitative Analytics Manager in the Performance Marketing Operations and Transformation team, you will design, implement, and optimize data-driven targeting strategies across owned advertising channels and email. You will build reusable audience and measurement assets that accelerate day-to-day execution while strengthening quality and consistency. You will help embed responsible artificial intelligence into marketing operations with strong governance, privacy, and traceability. You will work in a collaborative environment where your analyses translate directly into improved campaign outcomes. You will balance hands-on campaign support with longer-term transformation work, creating standards and tools that make targeting and measurement more scalable. You will help teams adopt “human-in-the-loop” ways of working so automation supports decision-making without compromising controls. You will also communicate results clearly—sharing what is working and where improvements will drive the most value.

Requirements

Bachelor’s degree in data science, statistics, information systems, or a related field.
Demonstrated hands-on experience in data analytics, customer segmentation, or targeting for marketing use cases.
Strong SQL skills with proven ability to manipulate data, validate outputs, and support scalable audience creation.
Working proficiency in Python for analysis and automation of repeatable data processes.
Experience translating business needs into clear technical requirements and success measures for delivery partners.
Practical understanding of digital marketing execution and performance measurement, including how targeting choices influence results.
Ability to identify appropriate automation opportunities, including responsible artificial intelligence use, while keeping scope controlled and outcomes measurable.
Strong communication skills with the ability to explain complex topics to non-technical partners and influence stakeholders.
Strong collaboration skills and experience working across marketing, sales, product, and technology teams.

Nice To Haves

Experience supporting marketing operations and marketing technology platforms, including hands-on activation and measurement workflows.
Familiarity with customer data platforms and marketing automation tools (for example: Salesforce, Segment, Adobe, SAS, or Microsoft solutions).
Experience integrating model scores or decision attributes into activation workflows in a controlled, governed manner where permitted.
Practical project management experience, including agile delivery and toolsets used for tracking work and dependencies.
Experience working with agencies or consultancies, including evaluating vendor claims and translating them into controlled implementation plans.
Ability to manage multiple initiatives under deadlines while maintaining quality, documentation, and strong controls.

Responsibilities

Develop and implement data management approaches that improve marketing execution, including automated data quality checks and streamlined documentation.
Analyze data from multiple systems to refine customer targeting and improve performance, using approved propensity, affinity, and suppression insights where applicable.
Build and maintain reusable assets (for example: audience templates, measurement views, and activation-ready datasets) to drive standardization and reusability.
Design repeatable quality assurance processes, including checklists and validation routines, to reduce manual effort and improve consistency.
Monitor and troubleshoot audience and data pipeline issues that impact sends, targeting accuracy, and performance.
Implement alerting and anomaly detection to proactively identify issues and reduce operational risk.
Partner with product and technology teams to define requirements for channel and data capabilities, ensuring measurable outcomes and clear controls.
Support development of controlled artificial intelligence capabilities (for example: segmentation, optimization, and workflow automation) aligned to governance and privacy expectations.
Quantify impact by tracking delivery efficiency, time saved through automation, and measurable performance improvements.
Share practical insights and recommendations using test-and-learn approaches and data-driven analysis.
Mentor junior analysts through coaching and hands-on feedback to build team capability and execution quality.