Principal Product Manager, Data Product & Data Science

Later is the enterprise leader in social media and influencer marketing software, services, and data, trusted by leading brands and agencies worldwide. Following our acquisition of Mavely, the Everyday Influencer Platform®, Later enables brands to scale creator partnerships from nano to premium influencers while managing social media content and campaigns across all major social and affiliate networks. Through proprietary performance data, marketing leaders can drive attributable sales and optimize social commerce with our software platform or award‑winning services.

Later is founded on two success stories that began in 2014:
Mavrck, the industry‑leading influencer marketing solution (now Later Influence™), and Later, the best social media management platform (now Later Social™) and first‑to‑market link in bio tool, Later Link in Bio. In 2024, Mavrck and Later officially joined together as one unified business, with a shared vision: to enable the world to make a living with their creativity.

We’re trusted by the top social platforms, with partnerships and integrations with Meta, Tik Tok, Linked In, You Tube, and Pinterest.

We enable marketers to create high‑performing content and engage in authentic collaborations with creators to reach new audiences, drive engagement, and generate predictable ROI.

Later’s biggest opportunity in the creator economy is turning our unique, multi‑source creator data into meaningful intelligence that drives better outcomes for brands, creators, and our internal teams. 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,…