Data Science / Analytics Manager, Weights & Biases

• Experience leading analytics or data teams in a fast-moving company
• Deep knowledge (practical and theoretical) of analytical and statistical techniques
• Comfort working with ambiguous problems and shaping them into concrete analyses
• History of writing easy-to-follow code and effective documentation for your projects
• Top 1% written communicator: ability to clearly communicate your ideas to folks across a range of backgrounds and levels of technical knowledge
• Comfort with data engineering best practices and workflows
• Outgoing and friendly: You'll love this role if you enjoy connecting with real users day to day, helping them solve issues and understand good patterns for using our tools. Day to day you'll be answering questions and requests with a kind, thoughtful tone that makes users feel appreciated and connected to our team
• Theoretical or practical knowledge of machine learning workflows and terminology

Desirable

• The Data group at Weights & Biases works across the full range of data-related topics:
• We help business partners set goals, make decisions, and understand the levers to achieve their goals
• We build reporting to keep the business attuned and aligned
• We build datasets and pipelines to support self-service analysis
• We train models to understand our customer growth, churn risk, and detect spam and abuse
• We’re exploring novel benchmarks and recs for model training
• We build and maintain a massive data platform to power it all
• As a Data Science and Analytics Manager, you’ll lead a small but mighty team of analysts and data scientists focused on helping W&B make better decisions with data
• You’ll partner closely with business leads to surface insights, build dashboards that clarify what’s happening in the business, and ensure our reporting and analysis is both accurate and actionable
• Your job is equal parts hands-on analysis, people leadership, and building systems so the team scales. You’ll report to the Head of Data, and sit next to our Data Platform and ML team members