Director, Data Science & AI

About the role

The Director of Data Science & AI will lead the team and efforts to turn data into decisions, deliver scalable intelligence that drives personalized experiences and business outcomes, and lean into AI and Automation where it makes sense. They will bridge the gap between what’s technically possible and what’s practically useful, setting the technical direction while being in the data, in the model reviews, and building alongside their team when it counts.

Your primary mission is to champion smarter ways of working and help both technical and non-technical teammates integrate AI into their everyday work, not as a disruption, but as a natural extension of how they already operate.

Responsibilities

• Own the data science roadmap for the organization from core statistical modeling and experimentation forecasting, segmentation and applied AI where it adds real business value
• Lead, mentor, and stay hands-on with a small team of data scientists: writing code and reviewing methodology, not just roadmaps
• Oversee the design of robust, production-grade solutions utilizing core cloud systems, vector databases, and agentic workflows
• Champion the adoption and continuous improvement of AI development tools across technical teams
• Scale MLOps/LLMOPs practices, ensuring data observability, governance, model safety, and ethical AI compliance
• Collaborate cross-functionally with Business Intelligence, Data Engineering, Analytics Engineering, Development, and Product teams to drive technical innovation, prioritize initiatives, ship MVPs fast and iterate based on usage data
• Design and run rigorous experiments to validate hypotheses and guide business decisions
• Translate statistical and technical work into business language for executive stakeholders and make the case for where data science investment should go next
• Define success metrics for internal tools and AI initiatives, and track adoption, usage, and business impact over time
• Document tools, workflows, and best practices to scale impact beyond individual engagements
• Stay informed on industry trends, viral content, and emerging platforms to identify new opportunities

Qualifications

• 7+ years in data science, including leading or managing a technical team
• Strong foundation in core data science
• Deep, hands-on fluency in Google Cloud Platform: BigQuery, Vertex AI, and building/deploying production models in a GCP environment
• Proficiency deploying custom Gemini Enterprise Agents via Agent Engine
• Fluency in AI tools such as Claude, CoPilot and ChatGPT
• Strong Python and SQL skills and experience in applied AI
• Bias for action