远程工作雷达

产品经理负责人, 数据与AI

Lead Product Manager, Data and AI

AI职能支持限定地区(需当地身份)
公司Lyrahealth
薪资未公开
工作地点United States
地域资格限定地区(需当地身份)
时区要求无特别要求
用工类型Full-time
发布时间未知
数据来源Lever
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注意地域限制:该职位明确限定在 United States 招聘。如果你是位于中国大陆的求职者,通常需要当地工作身份才能投递,或需与雇主确认是否接受独立合同(Contractor)形式合作。

Lyra Health 是一家领先的基于循证的心理健康护理服务提供商,与雇主合作为全球超过 2000 万人提供服务,并通过健康计划和合作伙伴关系覆盖超过 1 亿人。公司已提供超过 1500 万次心理健康护理,发表了 35 多篇同行评审的研究论文,在可及性、临床效果和成本效率方面取得了卓越成果。大量经过同行评审的研究证实,Lyra 的创新护理模式使人们恢复速度提高一倍,并且每年整体医疗费用索赔成本减少 26%。Lyra 通过 Lyra Empower 平台,将最高质量的护理与技术解决方案相结合,打造了唯一一个完全集成的 AI 驱动平台,从而改变人们对心理健康护理的获取方式。

关于该职位:

Lyra Health 正在寻找一位数据与 AI 首席产品经理,负责定义并推动我们下一代数据和人工智能项目的实施。在此职位上,您将领导跨机器学习模型和生成式 AI 项目中复杂产品功能的战略探索和端到端执行。您将与产品领导、工程团队和跨职能团队紧密合作,使数据成为企业核心资产,优化全球员工临床运营,提升会员体验,并扩大我们的竞争优势。

作为产品团队的关键成员,您将建立产品运营节奏,定义多年愿景,并将复杂的临床或业务需求转化为可扩展的数据和 AI 策略。您将与数据工程、数据科学、AI 基础设施和 AI/ML 工程团队深入合作,确保所有产品功能都遵循严格的临床证据、数据质量标准以及伦理和负责任的 AI 实践。

我们是平权雇主。我们不会基于种族、肤色、宗教、性别(包括怀孕)、国籍、年龄、残疾、基因信息或其他受法律保护的类别进行歧视。

通过申请此职位,您确认您的个人信息将按照 Lyra Health 的员工隐私通知进行处理。通过此申请,根据法律规定,我们将收集您的个人信息,包括但不限于您的姓名、电子邮件地址、性别认同、就业信息和电话号码,以用于该职位的招聘目的。

查看英文原文

About Lyra Health

Lyra Health is a leading provider of evidence-based mental health care, serving more than 20 million people globally in partnership with employers and more than 100 million through health plan and partner relationships. The company has delivered more than 15 million sessions of mental health care, published more than 35 peer-reviewed studies, and delivered unmatched outcomes in terms of access, clinical effectiveness, and cost efficiency. Extensive peer-reviewed research confirms Lyra’s transformative care model helps people recover twice as fast and results in a 26% annual reduction in overall healthcare claims costs. Lyra is transforming access to life-changing mental health care through Lyra Empower, the only fully integrated, AI-powered platform combining the highest-quality care and technology solutions.

About this role:

Lyra Health is looking for a Lead Product Manager for Data and AI to define and drive the next generation of our data and artificial intelligence initiatives. In this role, you will lead the strategy, exploration, and end-to-end execution of complex product capabilities across our machine learning models and generative AI initiatives. You will work closely with product leadership, engineering, and cross-functional teams to make data a core enterprise asset that optimizes global workforce clinical operations, elevates the member experience, and expands our competitive differentiation.

As a critical member of the Product team, you will establish product operating rhythms, define multi-year vision, and translate complex clinical or business demands into scalable data and AI strategies. You will partner deeply with Data Engineering, Data Science, AI Infrastructure, and AI/ML Engineering teams, ensuring all product capabilities follow rigorous clinical evidence, data quality standards, and ethical, responsible AI practices.

"We are an Equal Opportunity Employer. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, age, disability, genetic information or any other category protected by law.

By applying for this position, you acknowledge that your personal information will be processed as per the Lyra Health Workforce Privacy Notice. Through this application, to the extent permitted by law, we will collect personal information from you including, but not limited to, your name, email address, gender identity, employment information, and phone number for the purposes of recruiting and assessing suitability, aptitude, skills, qualifications, and interests for employment with Lyra.  We may also collect information about your race, ethnicity, and sexual orientation, which is considered sensitive personal information under the California Privacy Rights Act (CPRA) and special category data under the UK and EU GDPR.  Providing this information is optional and completely voluntary, and if you provide it you consent to Lyra processing it for the purposes as described at the point of collection, for example for diversity and inclusion initiatives.  If you are a California resident and would like to limit how we use this information, please use the Limit the Use of My Sensitive Personal Information form.  This information will only be retained for as long as needed to fulfill the purposes for which it was collected, as described above. Please note that Lyra does not “sell” or “share” personal information as defined by the CPRA. Outside of the United States, for example in the EU, Switzerland and the UK, you may have the right to request access to, or a copy of, your personal information, including in a portable format; request that we delete your information from our systems; object to or restrict processing of your information; or correct inaccurate or outdated personal information in our systems. These rights may be subject to legal limitations. To exercise your data privacy rights outside of the United States, please contact globaldpo@lyrahealth.com. For more information about how we use and retain your information, please see our Workforce Privacy Notice."

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.

Qualifications

  • 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.
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