Principal Product Manager

#paid•New York, NY

4d•$185,000 - $190,000

About The Position

You'll lead the product strategy for #paid's Data & ML organization, owning how data, signals, and ML-powered features drive measurable outcomes for brands and creators. You'll translate complex technical capabilities into user-facing product value while partnering closely with engineering, analytics, and business stakeholders to shape a defensible competitive advantage through AI-native, insight-driven capabilities. This is a net-new, foundational investment in our predictable performance roadmap and the Forge AI creator agent.

Requirements

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)
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

Nice To Haves

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

Responsibilities

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