Data & Marketing Systems Quant Analytics Lead-Senior Associate

Shape how marketing execution uses data-at scale and with strong controls-to deliver more relevant customer experiences.

In this role, you will modernize targeting data, reduce manual reporting through automation, and improve reliability with proactive monitoring.

You will partner across Product, Technology, and business stakeholders to bring measurable outcomes to life while enabling responsible use of artificial intelligence.

Job summary
As a Data Management Lead in the Marketing Execution team, you will design and run data strategies that improve audience targeting, measurement, and operational efficiency.

You will turn business needs into clear, testable requirements and repeatable datasets that support consistent delivery.

You will implement monitoring and quality checks to detect issues early and protect performance.

You will help teams adopt responsible "human-in-the-loop" ways of working for AI-supported execution.

You will quantify and communicate value through cycle-time reduction, hours saved, and audience quality improvements.

You will help establish reusable audience frameworks and documentation that accelerate delivery and reduce rework.

You will collaborate closely with Product and Technology to ensure new capabilities include clear controls, explainability expectations, and measurable success criteria.

You will build strong relationships across workstreams and drive adoption of best practices for standardization and reusability.
Job responsibilities


* Develop and implement data management strategies for marketing execution, including AI-assisted data quality monitoring and automated operational reporting to reduce manual effort and improve reliability


* Leverage data from systems of record to refine targeting and optimize performance, incorporating advanced analytics and machine learning-informed insights (for example, propensity and suppression inputs) where approved


* Drive adoption of best practices for standardization and reusability of marketing data outputs, including reusable audience frameworks and generative AI-accelerated documentation (requirements, definitions, quality assurance checklists)


* Manage execution, monitoring, and quality of data initiatives to support message-driven audience targeting, including proactive issue detection through alerts and anomaly flags


* Collaborate with Product and Technology to orchestrate requirements and delivery plans for product development, omnichannel initiatives, and system implementations, ensuring AI-enabled capabilities have clear controls and measurable outcomes


* Build strong working relationships across workstreams and stakeholders, and help drive adoption of human-in-the-loop operating models that enable safe scaling of AI-supported execution


* Partner with business leadership to define priorities and oversee execution, including quantifying value from automation and AI (cycle-time reduction, business-as-usual hours saved, audience q...