Lyra Health - Lead Product Manager, Data and AI
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Requirements
• Education: Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a related highly quantitative field. • Product Experience: 8+ years (Lead PM) of progressive product management experience within successful enterprise SaaS, cloud-based software, or health tech organizations, with a proven history of launching large-scale products with complex dependencies. • Data & AI Expertise: 3+ years of direct experience shipping machine learning and data-driven products at scale. Deep understanding of modern machine learning algorithms, deep learning techniques, generative AI use cases, and the infrastructure needed to deploy LLMs contextually. • Communication Skills: Exceptional written and verbal communication, narrative storytelling, and presentation skills; masterful ability to communicate complex algorithmic systems and technical trade-offs to non-technical executive teams and demanding corporate customer audiences. • Strategic Execution: Proven capacity to methodically unpack ambiguity, handle competing objectives, establish clear product boundaries, and maintain a calm, execution-oriented mindset in a fast-paced, high-velocity environment. • Healthcare Alignment (Nice-to-Have): Prior experience navigating a highly regulated industry (Healthcare Tech, FinTech) with an innate respect for data ethics, privacy constraints, and patient clinical quality. • $161,000 - $221,500 a year • As a full-time Lead Product Manager, you will be employed by Lyra Health, Inc. The anticipated annual base salary range for this full-time position is $161,000 to $221,500. The base range is determined by role and level, and placement within the range will depend on a number of job-related factors, including but not limited to your skills, qualifications, experience and location. This role may also be eligible for discretionary bonuses. • Annual salary is only one part of an employee’s total compensation package at Lyra. We also offer generous benefits that include: • Comprehensive healthcare coverage (including medical, dental, vision, FSA/HSA, life and disability insurances) • Lyra for Lyrians; coaching and therapy services • Equity in the company through discretionary restricted stock units • Competitive time off with pay policies including vacation, sick days, and company holidays • Paid parental leave • 401K with up to 3% matching • Monthly tech allowance • We like to spread joy throughout the year with well-being perks and activities, surprise swag, regular community celebration…and more! • We can’t wait to meet you.
Responsibilities
• Product Vision & Strategy: Define and champion a compelling multi-year product vision and roadmap for data and AI platforms, aligning technical milestones with Lyra's business growth, revenue objectives, and clinical goals. • GenAI & Modern Lifecycle Management: Drive high-impact opportunities leveraging generative AI, Large Language Models (LLMs), agentic AI, and advanced analytics, managing the entire lifecycle from ideation and rapid experimentation to scalable production deployment. • Cross-Functional Leadership: Collaborate extensively across complex matrixed stakeholder groups—including Product, Design, Engineering, Clinical Quality, and GTM teams—to embed smart AI capabilities directly into core member experiences and operations. • Responsible AI & Governance: Partner closely with Legal, Privacy, and Clinical leadership to maintain rigorous responsible AI practices • Impact Metrics & Optimization: Design robust measurement and experimentation frameworks (such as online controlled A/B testing) to track model effectiveness, quantify business outcomes, and evaluate trade-offs between tactical execution and long-term research. • Technical Team Collaboration: Translate unstructured business pain points into crisp, detailed product requirements, acting as a translator between highly technical data disciplines and non-technical business leaders. • Mentorship & Culture: Lead by example, mentoring junior team members, sharing technical product management best practices, and actively fostering a highly rigorous, data-driven culture across the product organization.
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