You will:

📍Partner closely with leads across Discovery, Search, Ads and Community teams to find improvements & opportunities using data science methodologies and tools. 📍Inform how to balance the needs across buyer demand, seller supply, launching new product categories and international markets. 📍Build actionable KPIs linking Northstar metrics to day-to-day operations. 📍Create production-quality dashboards and notebooks to convey insights for strategy and opportunities. 📍Improve engineering roadmaps through analysis of marketplace, user behavior, and industry trends. 📍Guide, oversee and improve experimentation practices to make decisions whether to rollout or rollback features. 📍Define and advance company best practices within a data-informed culture.

About You

📍We are looking for intellectually curious, highly motivated individuals to be foundational members of our Data team! You will partner with Product Engineering teams across Discovery, Search, Ads and Community domains to identify critical goals for the business, develop a deep understanding of them, and design scalable solutions enabled by both analysis and self-serve methodologies. 📍You should have strong critical thinking and analytical skills, excellent communication abilities, and a knack for working across teams in a fast-paced environment. The ideal candidate will be adept in navigating the data stack and able to support initiatives in all facets from metric creation to analytics engineering to basic modeling, ideally with previous experience in recommendation and relevance systems.. 📍In addition to 5+ years of experience in the Data field, you should have: 📍3+ years of experience in Data Analytics & Science supporting search and discovery systems. 📍Bachelor’s degree in Computer Science, Economics, Statistics, or a related field, or equivalent work experience. 📍Excellent verbal communications, including the ability to clearly and concisely articulate complex concepts to both technical and non-technical collaborators. 📍Industry experience with proven ability to apply scientific methods to solve real-world problems on large scale data. 📍Ability to lead initiatives across multiple product areas and communicate findings with leadership and product teams. 📍Comfortability with data warehouses and big data technologies such as Redshift, Snowflake, Big Query, Presto/Trino, Athena, Spark, DBT. 📍Expert in using SQL for data analysis, reporting, and dashboarding. 📍Experience with a scripting language such as Python or R. 📍Aptitude in goal setting, driver and cohort analysis. 📍Firm grasp of visualization tools, interactive and self-serving, such as business intelligence and notebooks.