
51 - 200 employees
🏪 Marketplace
📱 Media
🛍️ eCommerce
Marketplace • Media • eCommerce
#paid is a marketplace platform that connects creators with brands for marketing collaborations. It enables creators to find brand deals and helps marketers hire creators for campaigns. The platform focuses on building successful partnerships through creative strategy, live reporting, and post-campaign insights. #paid also allows brands to repurpose creator content across various marketing channels.
🔥 0 minutes ago
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51 - 200 employees
🏪 Marketplace
📱 Media
🛍️ eCommerce
Marketplace • Media • eCommerce
#paid is a marketplace platform that connects creators with brands for marketing collaborations. It enables creators to find brand deals and helps marketers hire creators for campaigns. The platform focuses on building successful partnerships through creative strategy, live reporting, and post-campaign insights. #paid also allows brands to repurpose creator content across various marketing channels.
• Own the end-to-end product vision for the Data & ML squad, including the Forge AI creator agent and predictive performance infrastructure • Translate complex ML/data capabilities into user-facing product value for both brands and creators • Partner with Data Product Engineering leads to align data product strategy with OKRs and drive commercial outcomes (NDR, retention, contribution margin) • Define the metrics layer: determine what we measure, how we surface insights, and connect metrics to business impact • Identify and prioritize ML-powered bets (creator-brand match quality, content performance prediction, churn signals) and drive them from conception to launch
• 6+ years of product management experience, with 2–3 years working directly with data, ML, or analytics products • Strong technical fluency with a prior engineering background (ex-engineer-turned-PM is the ideal archetype) • Hands-on experience writing or reviewing SQL; comfort navigating modern data warehouses (BigQuery, Snowflake, or similar) • Demonstrated track record shipping ML-adjacent features end-to-end (recommendations, ranking, prediction, scoring systems) • Working experience with LLMs or AI-native product workflows (prompting, agent design, RAG pipelines, etc.) • Clear ability to translate model outputs and data insights into compelling product narratives for non-technical stakeholders • Proven experience owning roadmaps tied to commercial outcomes (NDR, churn reduction, ARPU growth) • Familiarity with creator economy dynamics, marketplace mechanics, or two-sided platform product challenges is a strong plus • Experience building internal data tools and dashboards that empower ops and customer success teams • Deeply curious—the kind of person who explores the data warehouse for insights, not just on demand • Comfortable with ambiguity; you define the problem before being handed one • Can engage at multiple levels: hold technical depth conversations with engineers while presenting strategy to leadership • Build trust with engineering teams quickly; they want to build *with* you, not just have you manage them • High ownership mentality; thrive in lean, founder-adjacent environments.
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