We are seeking a highly strategic and results-oriented leader to lead our AI team. Reporting directly to the Vice President of Enterprise Data, Analytics, and AI, this is a critical leadership role responsible for defining and executing a comprehensive Data Science and AI strategy that serves all our business functions. The candidate will be a visionary leader with a proven track record of designing and deploying AI solutions at scale. This role is crucial for our organization's next phase of growth, as it will be responsible for building a common foundation for our Generative AI, Machine Learning, and Data Science initiatives to accelerate value delivery and prevent fragmented solutions. Responsibilities Develop AI Strategy: Help define and articulate a comprehensive enterprise AI strategy that aligns with business objectives and provides a unified approach to AI development and deployment. Team Leadership: Lead, mentor, and grow a team of high-performing AI practitioners (data scientists, ML engineers, statisticians) responsible for building and deploying production-ready AI solutions. Demand Prioritization: Working in partnership with the Enterprise AI Core Team to establish and manage a clear, repeatable process for prioritizing AI use cases from across the company, ensuring projects with the highest business value and strategic impact are selected. Build a Common Foundation: Architect and oversee the development of a unified AI platform and toolkit to serve as the foundation for all AI solutions, ensuring consistency, scalability, and efficiency. Stakeholder Management: Work in partnership with the portfolio management team to align with leaders from every business function to understand their needs, manage expectations, and evangelize the value of AI. Governance and Ethics: Work in partnership with the AI Governance team to enforce strong governance frameworks, including ethical AI principles and responsible use guidelines. Technology and Innovation: Stay abreast of the latest trends in Generative AI, machine learning, and data science, and lead the charge in adopting innovative technologies that create a competitive advantage. Deployment to Production: Guide the team in the end-to-end lifecycle of AI projects, from ideation and development to successful deployment, monitoring, and maintenance in a production environment. To accomplish this, partnering closely with the data engineering team in ensuring access to relevant, high-quality data. AI Literacy & Change Management: Drive the necessary organizational change by developing and implementing company-wide AI training and education programs to foster AI literacy, build internal capability, enable personal productivity, and ensure responsible, informed adoption of AI tools across all business functions in driving organizational effectiveness and efficiency.
Experience: 15+ years of experience in data science, machine learning, or a related field, with a proven track record of delivering impactful production systems with at least 10 years in a leadership role. Technical Skills & Platform Leadership: Enterprise AI/ML Proficiency: Deep expertise across the full spectrum of AI technologies, including classical Machine Learning, Deep Learning, and advanced Generative AI/Large Language Model (LLM) architectures (e.g., RAG systems, fine-tuning). MLOps Mastery: Proven ability to define and implement enterprise-grade MLOps frameworks, including automated model CI/CD pipelines, feature stores, model registries, and production monitoring/drift detection. Cloud and Data Foundation: Hands-on architectural experience with major cloud platforms (AWS, GCP, or Azure), specifically around managed data science services and scalable data pipelines (e.g., Spark, cloud data warehousing solutions). Programming and tools: Expert-level proficiency in programming languages like Python or R and extensive experience with ML libraries such as TensorFlow, Vertex AI, PyTorch, etc. Data Engineering: A strong background in data engineering with development experience in building data products/services in a cloud-based data platforms will be highly desirable. Roadmap Definition: Demonstrated ability to define a future-state technology roadmap that balances technical debt reduction with cutting-edge innovation in the AI space. Proven Track Record: Proven track record of leading multiple AI/ML programs from initiation through development and deployment with quantified success metrics. Strategic Thinking: Demonstrated ability to translate business challenges into actionable AI strategies and roadmaps Communication: Exceptional communication and presentation skills, with the ability to convey complex technical concepts to both technical and non-technical audiences. Leadership: Exceptional people leader with strong leadership and team-building skills, with a passion for mentoring and growing data science talent and fostering of continuous culture of innovation. Culture: Deeply passionate