Teams at The Zebra

Leads and develops product, marketing, and data analysts while overseeing analytics strategy, prioritization, technical standards, experimentation, reporting, and data quality. Partners with Product, Marketing, Finance, Engineering, and recruiting to deliver trusted insights, scalable self-service analytics, and team growth. Requires strong SQL and Python skills, modern data-tool experience, analytics leadership, stakeholder communication, and at least five years in data roles with two years managing teams.

Leads quality strategy and automated testing across functional, integration, and end-to-end applications. Owns test frameworks and infrastructure, integrates testing into CI/CD pipelines, plans release testing with Engineering and Product, tracks quality metrics, improves defect prevention, contributes to tooling standards, and mentors junior quality engineers.

Build and deploy machine learning models that personalize insurance products, analyze product data, design experiments, and measure model impact. The role owns the full data science lifecycle, including data wrangling, production coding, model monitoring, retraining, and experimentation. Responsibilities also include cross-functional collaboration, code reviews, mentoring data scientists, and improving platform practices.