Principal Product Manager, Data Product & Data Science

Posted 2 days agoViewed
210000 - 250000 USD per year
United States, CanadaFull-TimeCreator Economy, Social Media
Company:Later
Location:United States, Canada
Languages:English
Seniority level:Principal, 8+ years
Experience:8+ years
Skills:
LeadershipProject ManagementPythonSQLData AnalysisMachine LearningProduct ManagementStrategyData engineeringData science
Requirements:
8+ years of product management experience, with meaningful ownership of data-heavy or platform-level products Demonstrated experience building or scaling data products Hands-on comfort with data tools and concepts (e.g., SQL, BigQuery, analytics workflows) Experience working alongside data science teams on algorithms, modeling, or applied ML Proven ability to zoom out to the strategic narrative and zoom in to the weeds Strong stakeholder management skills and a track record of influencing senior leaders in ambiguous environments Experience at a data-first or analytics-driven company (Nice to have) Exposure to social platforms, creator economy products, advertising technology, or agency environments (Nice to have) Familiarity with programmatic advertising, marketplace dynamics, or matching/recommendation systems (Nice to have)
Responsibilities:
Own and evolve the end-to-end creator data product strategy Define and maintain a long-term roadmap for creator and audience data Identify high-leverage data opportunities Translate business problems into data product bets Partner closely with Data Engineering and Data Science Drive improvements to creator-level data Define and track a Data Quality Score and related KPIs Work hands-on with datasets using SQL and analytics tools Guide development of data-derived insights Serve as a trusted product partner to various teams Align cross-functional stakeholders Act as the connective tissue between technical teams and business leaders Influence without authority Set a high bar for data product thinking Mentor other product managers on data literacy Champion a culture of curiosity, accountability, and customer-driven decision-making Stay ahead of emerging trends in data products, applied ML, creator analytics, and measurement Continuously assess new data sources, modeling approaches, and tooling
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