About the company
Whatnot is a livestream shopping platform and marketplace backed by Andreessen Horowitz, Y Combinator, and CapitalG. We’re building the future of ecommerce, bringing together community, shopping and entertainment. We are committed to our values, and as a remote-first team, we operate out of hubs within the US, Canada, UK, and Germany today. We’re innovating in the fast-paced world of live auctions in categories including sports, fashion, video games, and streetwear. The platform couples rigorous seller vetting with a focus on community to create a welcoming space for buyers and sellers to share their passions with others.
Job Summary
Role
📍Partner closely across the business to find improvements/opportunities and influence decisions using data science methodologies and tools 📍Build actionable KPIs, create production-quality dashboards and notebooks to convey insights 📍Define and advance best practices within an experiment-driven culture 📍Inform product engineering roadmap through analysis of marketplace, user behavior, and product trends
About You
📍We are looking for intellectually curious, highly motivated individuals to be foundational members of our Data team! You will partner with our Engineering, Product, Finance and Operations teams to identify critical goals for the business, develop a deep understanding of them, and design scalable solutions. 📍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 analytics/data engineering and product analytics to machine learning. 📍In addition to 6+ years of experience in the Data Analytics field, you should have: 📍Excellent verbal communications, including the ability to clearly and concisely articulate complex concepts to both technical and non-technical collaborators 📍Bachelor’s degree in Computer Science, a related field, or equivalent work experience. 📍Demonstrated history of knowledge in Business 📍Analysis, Statistics, Mathematics, Economics or related technical fields 📍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, Athena, Spark, DBT 📍Expert in using SQL for data analysis, reporting, and dashboarding 📍Experience with a scripting language such as Python or R 📍Aptitude and experience in applied statistical modeling and machine learning techniques 📍Firm grasp of visualization to
