Whatnot is a community marketplace where you can buy, sell, go live and geek out with collectors and other like-minded people. Today’s online marketplaces are neither safe nor fun -- they’re full of counterfeits, and you shop by endlessly scrolling through listings. Whatnot verifies every item sold and provides a fun social shopping experience to enjoy with friends and community members.
Whatnot is backed by some of the industry’s best venture capital investors, including Y Combinator, Scribble.vc, Liquid 2 Ventures, and Wonder Ventures.
Skills: Python, SQL, Machine Learning, Data Modeling, Data Analytics
We are looking for intellectually curious, highly motivated individuals to be foundational members of our Data Science and Machine Learning team. You will partner with our Engineering, Product, 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 data engineering and product analytics to machine learning and service deployments.
The team is distributed across the country, but headquartered in Los Angeles, CA. This role may be remote with preference for Pacific time zone. A relocation package is available for candidates who are interested and qualify.
- Partner closely across the business to find improvements and influence decisions using data science methodologies and tools
- Enrich product and operations with new kinds of machine learning powered experiences
- Design and implement end-to-end data pipelines and data systems that support MLOps and business processes
- Build actionable KPIs, create production-quality dashboards and notebooks to convey insights
- Define and advance best practices within an experiment driven culture
- Excellent verbal communications, including the ability to clearly and concisely articulate complex concepts to both technical and non-technical collaborators
- Demonstrated history of knowledge in Computer Science, Statistics, Mathematics, Software Engineering 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
- Experience with operational databases such as PostgreSQL, DynamoDB
- Comfortability with data warehouses and big data technologies such as Redshift, Snowflake, Big Query, Presto, Athena, Spark, DBT
- Extensive experience with Python and SQL for software development, data analysis, and machine learning
- Aptitude and experience in applied statistics and machine learning techniques
- Firm grasp of visualization tools interactive and self-serving such as business intelligence and notebooks
- Familiarity with cloud computing platforms such as AWS or GCP
- Experience launching production-quality machine learning models at scale e.g. dataset construction, preprocessing, deployment, monitoring, quality assurance
Compensation & Benefits
Top-quality healthcare benefits, generous parental leave, unlimited vacation policy, lunch, internet & cell phone expensed, competitive salary, equity. Relocation assistance available upon meeting criteria.
Infrastructure: AWS, Kubernetes, Serverless
Databases: Postgres, DynamoDB, ElasticSearch, Redis
Backend: Python (Flask), Node, Elixir
Front-End React, React Native, Swift, Kotlin