VP of Data and AI

Lyra Health · United States

About Lyra Health
 
Lyra Health is the leading provider of mental health solutions for employers supporting more than 20 million people globally. The company has delivered 13 million sessions of mental health care, published more than 20 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.

We are seeking a visionary and results-oriented VP of Data and AI to lead our AI and machine learning initiatives, data strategy and advanced analytics, driving significant business impact across the organization. This role reports into our CPTO.

Role Summary

The VP of Data and AI will be a key leadership role, responsible for defining, developing, and executing the company's comprehensive data and AI strategy. This leader will build and manage world-class Data Engineering, Data Science, Data Analytics, AI Platform and AI/ML Engineering teams, ensuring data is a core asset that informs all strategic decisions, optimizes operations, and creates new revenue streams. The ideal candidate is a strategic thinker with deep technical expertise, exceptional leadership skills, and a proven track record of delivering measurable business value through data and AI.

 

Responsibilities:

Strategy and Vision

  • Define and champion the company's multi-year data and AI strategy, aligning it with overall business objectives and growth plans.

  • Identify high-impact opportunities for leveraging generative AI, machine learning and advanced analytics across product development, operations, sales, and marketing.

  • Establish data governance policies, data quality standards, and ethical AI practices to ensure data integrity, security, and compliance.

    • Team Leadership and Development

    • Recruit, mentor, and lead high-performing teams of Data Engineers, Data Analysts, Data Scientists, AI Infra, AI and ML Engineers.

    • Foster a data-driven culture across the organization, promoting data literacy and the use of analytical insights in daily decision-making.

      • Execution and Delivery

      • Oversee the architecture, development, and maintenance of scalable and reliable data platforms (e.g., data warehouse, data lake, ML and AI Platform infrastructure).

      • Drive the end-to-end lifecycle of AI/ML projects, from ideation and experimentation to deployment, monitoring, and measurable business impact.

      • Manage budgets, technology selection, and vendor relationships related to data and AI infrastructure and tooling.

        • Cross-Functional Collaboration

        • Partner closely with Product, Engineering, Clinical and Operations leaders to embed data and AI capabilities into core products and business processes.

        • Act as the primary evangelist for data and AI capabilities internally and externally.

        • Present strategy, roadmaps, and key results to the executive team and board of directors.

Qualifications:

Required Experience

  • 10+ years of progressive experience in AI, machine learning, data science, data engineering, or a related field, with 5+ years in a senior leadership role (Sr Director, VP) managing large, diverse technical teams.

  • Proven experience defining and executing a successful enterprise-wide data and AI strategy that delivered significant, quantifiable business outcomes.

  • Deep expertise in modern data architecture, cloud-based data platforms (ideally AWS), data warehousing (ideally Snowflake), and ETL/ELT processes.

  • Extensive experience with the entire machine learning and GenAI lifecycle, delivering to users at scale

    • Technical Skills

    • Deep understanding of generative AI models, LLMs and their practical application in a business context.

    • High proficiency in programming languages (Python, SQL).

    • Solid understanding of statistical modeling, machine learning algorithms, and deep learning techniques.

      • Leadership and Soft Skills

      • Exceptional communication and presentation skills, with the ability to articulate complex technical concepts to a non-technical executive audience.

      • Strong business acumen and the ability to translate technical concepts into strategic business opportunities.

      • Demonstrated ability to attract, hire, retain, and develop top-tier technical talent.

      • Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Statistics, or a related quantitative field.

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