Marketing Data Science Analytics Lead

eBay•San Jose, CA

2d•$170,400 - $227,500

About The Position

The Marketing Data Science Analytics Lead will build customer intelligence, AI-powered targeting, and CRM optimization at eBay. The role defines measurement strategies, guides personalization and experimentation, and influences CRM investment decisions across buyer, seller, and company-wide initiatives. It offers broad cross-functional exposure and the opportunity to help develop an inclusive, high-performing analytics culture while improving customer experiences. The role is part of the CRM Data Science Analytics team, which partners with Marketing, Product, and Engineering to use customer data to inform strategic decisions and compose, measure, and optimize CRM programs that deepen engagement, strengthen customer dedication, and accelerate growth across the customer lifecycle.

Requirements

Proven experience leading CRM, marketing, or customer analytics initiatives that deliver measurable business outcomes in e-commerce, marketplace, subscription, consumer technology, or similar customer-focused environments.
Deep expertise in analytics, machine learning, and AI applications for CRM and personalization, including churn prediction, propensity modeling, CLV/LTV forecasting, uplift modeling, recommendations, and decisioning systems.
Strong foundation in experimentation and statistical methods, including experimental build, power analysis, variance reduction, causal inference, and measurement guidelines.
Advanced proficiency in SQL and Python for large-scale analysis, modeling, automation, and analytics engineering within modern data environments and version-controlled workflows.
Strong business judgment and communication skills, with the ability to convert complex insights into clear recommendations and persuade cross-functional partners and senior leaders.
Experience working with AI-powered products, CRM or marketing technology platforms, customer journey tools, event-level behavioral data, and modern data and AI ecosystems such as Spark, Databricks, Airflow, and Claude Code.

Responsibilities

Define success metrics, learning agendas, and optimization frameworks that connect CRM investments to retention, engagement, revenue growth, and customer lifetime value.
Develop and improve machine learning models for targeting and personalization, including propensity, churn, uplift, recommendation, and next-best-action models.
Lead A/B and multivariate testing and causal measurement for CRM programs to generate actionable insights and accelerate learning.
Build scalable analytics and AI solutions, including automated data pipelines, reusable datasets, and self-service tools.
Recommend data-driven approaches to targeting, content, frequency, and customer journey development across email, push, in-app, onsite, and lifecycle channels.
Translate analytical findings into business recommendations and influence cross-functional partners and senior leaders.
Mentor team members and strengthen team capabilities through mentorship and established guidelines.