VP of Data and AI

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.

• 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.

• 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.

• 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.

• 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.

• 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

• 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.

• 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.