About the company
Whatnot is a livestream shopping platform and marketplace backed by Andreessen Horowitz, Y Combinator, and CapitalG. Weāre 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. Weāre 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
šPartner closely across the business to find improvements/opportunities and influence decisions using data science methodologies and tools šBuild actionable KPIs, create production-quality dashboards and notebooks to convey insights šDefine and advance best practices within an experiment-driven culture šInform product engineering roadmap through analysis of marketplace, user behavior, and product trends
About You
šWe 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. šYou 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. šIn addition to 6+ years of experience in the Data Analytics field, you should have: šExcellent verbal communications, including the ability to clearly and concisely articulate complex concepts to both technical and non-technical collaborators šBachelorās degree in Computer Science, a related field, or equivalent work experience. šDemonstrated history of knowledge in Business šAnalysis, Statistics, Mathematics, Economics or related technical fields šIndustry experience with proven ability to apply scientific methods to solve real-world problems on large scale data šAbility to lead initiatives across multiple product areas and communicate findings with leadership and product teams šComfortability with data warehouses and big data technologies such as Redshift, Snowflake, Big Query, Presto, Athena, Spark, DBT šExpert in using SQL for data analysis, reporting, and dashboarding šExperience with a scripting language such as Python or R šAptitude and experience in applied statistical modeling and machine learning techniques šFirm grasp of visualization to
