Principal Product Manager, Later

• 8+ years of product management experience, with meaningful ownership of data-heavy or platform-level products
• Demonstrated experience building or scaling data products, not just dashboards—schemas, pipelines, signals, or models that power downstream use cases
• Hands-on comfort with data tools and concepts (e.g., SQL, BigQuery, analytics workflows) and the ability to engage deeply in the details
• Experience working alongside data science teams on algorithms, modeling, or applied ML—even if you were not the primary model builder
• A proven ability to zoom out to the strategic narrative and zoom in to the weeds when necessary
• Strong stakeholder management skills and a track record of influencing senior leaders in ambiguous environments

Desirable

• As Principal Product Manager, Data Product & Data Science, you will own the strategic data product roadmap that powers how creators are understood, evaluated, and matched to the right brand opportunities
• This is a net-new, highly visible role reporting directly to the Chief Product Officer
• You will operate at the intersection of product strategy, data engineering, data science, and go-to-market teams—shaping how raw data becomes trusted signals, differentiated insights, and defensible competitive advantage across Later’s platform, agency, and services offerings
• Own and evolve the end-to-end creator data product strategy, spanning data acquisition, enrichment, modeling, quality, and insight generation
• Define and maintain a long-term roadmap that improves the breadth, depth, freshness, and reliability of creator and audience data across all internal and external sources
• Identify high-leverage data opportunities that unlock differentiation for Sales, Strategy, and Agency teams—turning data into a compelling narrative brands can buy into
• Translate ambiguous business problems into clear data product bets, success metrics, and sequencing decisions
• Partner closely with Data Engineering and Data Science to shape schemas, pipelines, models, and feature sets that support scalable data products
• Drive improvements to creator-level data including (but not limited to): social content signals, audience attributes, campaign performance metrics, Link in Bio behavior, commerce outcomes, and historical brand partnerships
• Define and track a Data Quality Score and related KPIs that quantify completeness, accuracy, timeliness, and usability
• Work hands-on with datasets using SQL and analytics tools to validate assumptions, explore opportunities, and pressure-test solutions
• Guide development of data-derived insights that improve brand–creator matching, campaign planning, and performance prediction
• Serve as a trusted product partner to Strategy, Sales, Agency/Services, Search, Campaigns, Reporting & Analytics, and Platform Services teams
• Align cross-functional stakeholders around shared definitions, priorities, and tradeoffs for data initiatives
• Act as the connective tissue between technical teams and business leaders—ensuring data products are both technically sound and commercially meaningful
• Influence without authority, using clarity, data, and strong product judgment to move teams forward
• Set a high bar for data product thinking, rigor, and storytelling across the Product organization
• Mentor other product managers on data literacy, experimentation, and outcome-oriented product discovery
• 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 that could strengthen Later’s competitive position
• Bring external best practices into the organization while adapting them to Later’s scale and business model
• What success looks like:
• Measurable improvement in creator data quality, coverage, and freshness, reflected in a consistently rising Data Quality Score
• Internal teams trust and actively use creator data to make decisions about matching, pricing, strategy, and campaign design
• Brands see clearer differentiation in how Later helps them identify the right creators—not just popular ones—for their goals
• Sales and Strategy teams are equipped with data-backed stories that elevate conversations from execution to insight
• Product, Data Engineering, and Data Science teams operate with shared clarity on priorities, metrics, and outcomes
• Driven by Impact: You deliver results that matter—prioritizing high-value work, meeting deadlines, and adapting quickly while keeping outcomes clear
• Strategic & Customer-Centric: You anticipate risks and opportunities, connect decisions to long-term growth, and build trust through proactive insights
• Curious & Growth-Oriented: You seek knowledge, ask sharp questions, and apply learnings fast—challenging the status quo with a mindset of improvement
• Collaborative & Resilient: You thrive in change by staying resourceful, solution-focused, and positive—removing roadblocks, sharing insights, and keeping morale high
• Accountable & Honest: You own your work, hold yourself and others to a high bar, and use transparent feedback to drive growth
• Emotionally Intelligent: You build trust through empathy and collaboration, foster inclusion, and inspire others with grit, optimism, and integrity