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Mid-level senior title, metro location, and popular program role increase applicant competition.
Requires embedded data/ML program experience, making cross-industry transferability limited.
Mandatory 5+ years plus 2+ years data-embedded experience and ML lifecycle knowledge raises strictness.
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Lead end-to-end program management for multi-team data platform and data science initiatives, including migrations and AI-powered product launches.
Develop and maintain program roadmaps, milestones, and delivery timelines while managing risks and tracking program health with status updates and dashboards.
Coordinate cross-functional stakeholders across engineering, product, operations, and finance to ensure alignment, resource planning, and operational excellence in data and ML programs.
5+ years of technical program management experience, with at least 2 years in data, analytics, or ML engineering organizations.
Strong understanding of modern data stack concepts such as ELT pipelines, data warehousing, and analytics engineering.
Experience managing ML or data science programs across the ML lifecycle including data preparation, experimentation, model training, deployment, and monitoring.
Ability to work onsite in an office-first model at least four days a week in Metropolis's corporate location.
Experienced in coordinating complex, cross-functional data and ML programs involving multiple teams and stakeholders.
Capable of translating technical concepts for executive audiences and defining actionable technical requirements for engineering teams.
Comfortable operating with ambiguity and driving program structure and delivery in fast-growth or startup environments.