Product Manager II, Match

Spring Health
New York (Hybrid)$123k – $165kPosted 26 March 2026

Job Description

Our mission: to eliminate every barrier to mental health. At Spring Health, we’re on a mission to revolutionize mental healthcare by removing every barrier that prevents people from getting the help they need, when they need it. Our clinically validated technology, Precision Mental Healthcare , empowers us to deliver the right care at the right time—whether it’s therapy, coaching, medication, or beyond—tailored to each individual’s needs. We proudly partner with over 450 companies, from startups to multinational Fortune 500 corporations, as a leading provider of mental health service, providing care for 10 million people. Our clients include brands you use and know like Microsoft, Target, and Delta Airlines, all of whom trust us to deliver best-in-class outcomes for their employees globally. With our innovative platform, we’ve been able to generate a net positive ROI for employers and we are the only company in our category to earn external validation of net savings for customers. We have raised capital from prominent investors including Generation Investment, Kinnevik, Tiger Global, Northzone, RRE Ventures, and many more. Thanks to their partnership and our latest Series E Funding, our current valuation has reached $3.3 billion. We’re just getting started—join us on our journey to make mental healthcare accessible to everyone, everywhere. 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. Please note that this is a hybrid role based in New York City , with an expectation to be in the office 2-3 days a week at our 60 Madison Avenue location. What you’ll do: 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 What You’ll Bring: 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 perform ... (truncated, view full listing at source)
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