Set Vision & Strategy: Define and evolve the enterprise AI/ML technology product strategy, aligning it with business objectives, change management, responsible AI expectations, and emerging industry trends.

Product Leadership (Platform & Tooling): Guide the creation and delivery of infrastructure, tooling, and platforms that enable scalable, secure, and efficient AI/ML model development and deployment.

Drive productivity, sophistication, and speed outcomes in areas such as: Model development & experimentation: notebook/IDE experience, experiment tracking, model registry, reusable templates Training & compute enablement: scalable training patterns, environment provisioning, performance optimization, cost transparency Deployment & serving: batch/real-time inference enablement, CI/CD for ML, rollout/rollback patterns, monitoring/observability Prompt-based solutions enablement (where applicable): evaluation frameworks, version control, deployment, lifecycle management, governance and guardrails Platform adoption & developer experience: documentation, enablement, self-service onboarding, internal community feedback loops Bachelor's degree in a quantitative field with 10+ years of related experience in data/data science or technology product management Prior experience effectively managing large teams Master's degree preferred Preferred:

Experience: with Snowflake and/or Databricks, AWS, and/or Airflow in enterprise data/AI environments Preferred:

Experience: working in Financial Services (or similarly regulated environment) within a large, matrixed organization