Director of Product Management, Weights & Biases

• We are seeking an experienced Director of Product Management to lead the development of our platform infrastructure, identity management, and enterprise-focused platform
• If you have a passion for solving challenges at the intersection of infrastructure and enterprise needs, and a proven track record in delivering impactful solutions across diverse architectures, we’d love to hear from you!
• 4+ years of product management experience for an enterprise software product
• Have a deep understanding of enterprise IT requirements and and experience working directly with large enterprises to deploy software consistent with their architectures (e.g. experienced with authentication, authorization, data retention, security audits, etc.)
• Experience making a technical product better, especially improving the developer experience
• Experience driving the end-to-end product lifecycle, working autonomously to conduct user interviews, dig in on metrics, define requirements, run a process with engineering to deliver the product, measure success, and iterate. You partner with your engineering colleagues, and sweat the details to ensure they have a clear and efficient plan of execution
• Previous experience in a leadership or managerial role, with a track record of effectively managing and growing teams

Desirable

• In this role, you will own the product vision and strategy for our platform offerings across multi-tenant, single-tenant, and on-premises customer-managed deployments
• Reporting to the Vice President of Product, you will collaborate with cross-functional teams to design and deliver secure, scalable, and innovative solutions that meet the demands of enterprise clients. Your ability to navigate complex product ecosystems and align technical initiatives with business objectives will be critical in shaping our platform's future and driving customer success
• Your ability to navigate complex product ecosystems and align technical initiatives with business objectives will be critical in shaping our platform's future and driving customer success
• You will partner closely with the Engineering and Go-To-Market Teams to improve the enterprise customer experience
• You will explore complex and exciting technical problems across our stack from the Python client to the web app across different deployment offerings. You will have the opportunity to work on products across the ML lifecycle, including experiment tracking, dataset management, and model optimization
• Personas: Understand our core user's workflow, dig in on where AI practitioners spend their time, and who else on their teams they interface with
• Metrics: Dig into existing metrics, identify opportunities to measure user behavior better, and drive projects to capture better metrics. Investigate patterns of user behavior that predict activation, retention, sharing, and conversion to paying customers
• Interviews: Meet with users and customers and run usability studies to uncover issues and validate hypotheses on how to improve our product funnel
• Analysis: Analyze the lifecycle of a standard user, and identify how we can show value quickly, capture their daily workflow, and retain our enterprise customers Test the product, and run through common workflows manually, both in the app and in the client library
• Collaboration: Work cross-functionally with growth, sales, customer success, ML practitioners, and engineers. Gain insights and communicate hypotheses, goals, and findings in conversations across teams
• Experiments: Define experiments with clear metrics, spec product, and marketing projects, and own taking the project from inception to launch. Scope projects that include work across surfaces from the web app and client library to documentation, the marketing site, and email campaigns. Work closely with the engineering and growth teams to implement changes, and measure outcomes of A/B tests to identify effective improvements
• Commercialization: Identify improvements to the user conversion funnel, and make tactical changes to smooth the transition from signing up as a free user to paying for a team, then upgrading to more advanced plans, including both in-product conversion and/or hand-offs to sales
• Iterations: Revisit successful experiments, and identify if there are opportunities to double down and invest more time in execution