Lead Product Operations Manager (Data)

New

Fully remote options within the United StatesFull-TimeLead

SalaryRemote Standard: $136,000–$179,000 base salary, plus equity and bonus opportunities. New York City: $158,000–$209,000 base salary, plus equity and bonus opportunities. Remote Premium: $143,000–$189,000 base salary, plus equity and bonus opportunities.

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Job Details

Experience: 6–10 years of experience
Required Skills: Project ManagementMachine LearningProduct Operations

Requirements

Have 6–10 years of experience in product operations, business operations, program management, or a closely related field.
Demonstrate success supporting large, complex, cross-functional organizations in Product Operations, Program Management, or similar roles.
Apply root-cause analysis and first-principles problem-solving to identify risks, develop practical solutions, and resolve impediments.
Navigate ambiguity independently, prioritize competing demands, and drive initiatives to completion.
Manage multiple initiatives and priorities using strong organizational and project-management capabilities.
Understand business objectives and product strategies and translate them into operational priorities.
Be familiar with project and delivery methodologies and apply appropriate approaches to complex initiatives.
Have strong analytical skills and work with teams to define KPIs aligned with strategic priorities.
Have experience partnering with data analysts or analytics teams to develop performance dashboards.
Demonstrate data acumen, attention to detail, and commitment to data quality and process hygiene.
Collaborate effectively across technical and non-technical functions and build trusted stakeholder relationships.
Experience with machine learning, AI-powered products, experimentation, or data-driven product operations is highly relevant.

Responsibilities

Identify and address friction throughout the product lifecycle, from discovery and planning through launch and ongoing improvement.
Lead and support operational initiatives for machine learning model launches and AI-powered product features across multiple product squads.
Improve cross-functional processes, workflows, and operational hygiene to support consistent execution and team alignment.
Support adoption of better tooling and practices for A/B experimentation across functions.
Coordinate contributors and stakeholders, aligning expectations, responsibilities, and timelines.
Monitor KPIs and OKRs and provide data-driven insights to support operational decisions.
Partner with data and analytics teams to establish KPIs and maintain accurate, actionable dashboards and reporting.
Translate performance trends and operational data into recommendations for assigned teams.
Help manage and optimize product technology and collaboration tools, including roadmapping and team workflow platforms.
Contribute to quarterly planning and connect squad priorities with organizational strategy.

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