Product Manager, Spring Health

• 2–4 years of product management experience, or equivalent experience working on software products
• Strong execution skills: ability to break down problems, prioritize work, and deliver incrementally
• Analytical mindset: comfortable interpreting product metrics, user behavior, and experiment results
• Experience working closely with engineering teams to ship complex products
• Clear written and verbal communication, especially in cross-functional settings
• Experience partnering with data scientists and ML engineers to build, evaluate, and launch ML-driven product solutions that address user needs and deliver measurable business impact
• Comfort with learning how ML systems work, asking good questions, and collaborating with technical partners
• Ability to reason about model performance, evaluation, and trade-offs
• Not sure if you meet every requirement? Research shows that women and people from historically underrepresented communities often hesitate to apply for roles unless they meet every qualification compared to other similarly-qualified candidates. If this role excites you, we encourage you to apply.

Desirable

• Reporting to the Group Product Manager, Care Orchestration, this full-time Product Manager II will be immersed in the mission-critical work of the Match pod
• This team is at the forefront of leveraging Machine Learning and in-care intelligence to connect members with the right provider and care pathway, directly influencing clinical outcomes and the member experience
• It is an execution-heavy role that will challenge you to deepen your product craft in AI-driven healthcare systems
• Own the end-to-end product lifecycle for your pod, from problem definition through delivery and iteration
• Translate ambiguous user and business problems into clear product requirements and prioritized roadmaps
• Partner closely with Engineering, Data Science, and Design to define solutions, trade-offs, and delivery milestones
• Use data, experimentation, and customer insight to inform product decisions and measure impact
• Work with ML engineers and data scientists to define goals, data needs, evaluation methods, and quality gates
• Identify opportunities where AI/ML can solve real user problems and deliver measurable value
• Build strong, trust-based relationships with cross-functional partners across product teams
• What success looks like:
• High-quality features and improvements ship consistently and improve key metrics (e.g., conversion, retention, care quality)
• ML-powered capabilities you support are well-scoped, measurable, and improved through iteration
• You are a reliable execution partner who unblocks the team and drives clarity in ambiguous spaces
• You’re known as a strong collaborator across product, engineering, and data science