VP of Data and AI
New
United StatesFull-TimeVp
Salary$251,000 - $346,000 a year
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Job Details
- 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
- Required Skills
- AWSPythonSQLETLMachine LearningSnowflakeData engineeringData scienceGenerative AI
Requirements
- 10+ years of progressive experience in AI, machine learning, data science, data engineering, or a related field.
- 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.
- Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Statistics, or a related quantitative field.
Responsibilities
- 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.
- Oversee the architecture, development, and maintenance of scalable and reliable data platforms.
- Drive the end-to-end lifecycle of AI/ML projects, from ideation and experimentation to deployment, monitoring, and measurable business impact.
- Partner closely with Product, Engineering, Clinical and Operations leaders to embed data and AI capabilities into core products and business processes.
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