Senior Product Manager - Platform Growth & Scaling

Role Description

We are looking for a technically fluent Sr. Product Manager who combines marketplace growth instincts with enough technical depth to work directly with engineering — reading data, navigating codebases, and making architecture tradeoffs without needing a translator.

This role has two phases:

• Phase 1 — Platform Stabilization (Months 1–6)
  • Own the contributor onboarding redesign: reduce sign-up-to-first-task from 30 minutes to under 3 minutes by simplifying identity verification, certification, and task matching.
  • Work directly with engineering on legacy architecture decisions — understand data flows, surface tradeoffs, and advocate for solutions without requiring engineering to translate for you.
  • Define and track platform health metrics: activation rate, time-to-first-task, task completion rate, payment cycle time, contributor satisfaction score.
  • Establish a fast feedback cadence with engineering: review shipped features in dev environments, provide same-day input, reduce sprint cycle drag.
• Phase 2 — Social Platform Build (Months 6+)
  • Design and own the algorithmic task feed: a personalized interface where contributors discover tasks, micro-learning content, and peer activity matched to their skills and history.
  • Build the contributor identity layer: public AI expertise profiles with verified accuracy rates, domain certifications, skill badges, and shareable portfolio artifacts.
  • Design PLG growth loops: content share mechanics, peer validation referral bonuses, and cohort-based project matching to drive organic contributor acquisition.
  • Lead gamification systems: streaks, tier progression, leaderboards, and certification unlocks designed to drive daily return behavior, not just one-time activation.
  • Collaborate with data science on the matching and recommendation engine: contributor-to-task routing, dynamic pricing, and cold-start solutions for new contributor segments.
• Cross-Functional & Strategic
  • Partner with AVP of Product to define the roadmap balancing stabilization, growth, and enterprise B2B requirements.
  • Work with enterprise sales to translate client requirements — specialized contributor segments, domain certifications, rapid turnaround SLAs — into platform capabilities.
  • Define North Star metrics across both sides of the platform: DAU/WAU, session depth, task completion rate, data pipeline volume, match accuracy.
  • Build and mentor product success team members as the function grows.

Qualifications

• 5–8 years of product management experience in consumer platforms, marketplace products, or growth-focused roles.
• Proven track record designing and shipping growth loops with measurable activation, retention, or referral outcomes — not just funnel optimization.
• Experience with two-sided or multi-sided marketplace dynamics: contributor/creator activation, supply/demand balancing, liquidity mechanics.
• Hands-on experimentation: A/B test design, holdout groups, guardrail metrics, statistical significance — owning the full cycle from hypothesis to roadmap decision.
• Experience working with distributed engineering teams across timezones: able to communicate requirements precisely in async formats and maintain momentum without synchronous dependency.

Requirements

• SQL proficiency: writes and interprets queries independently for funnel analysis, cohort breakdowns, and experiment readout.
• Comfortable navigating codebases and using AI coding tools (Claude Code, Cursor, Copilot) to demo features, review shipped work, and reduce discovery dependency on engineering.
• Working knowledge of APIs, data flows, and system architecture — able to identify where technical debt creates product risk and communicate tradeoffs clearly to engineering leadership.
• Able to participate in ML/data science discussions on model inputs, signal design, and experiment methodology — not required to build models, but required to spec and evaluate them.

Skills & Mindset

• PLG & viral mechanics: designs referral loops, social sharing triggers, and network-driven onboarding — not just onboarding checklists.
• Gamification: experience with streak mechanics, badge systems, tier progression, or engagement loops that drive habitual return behavior.
• Bias to action: ships MVPs quickly, iterates on real signal, comfortable with ambiguity and incomplete data.
• User-centric: obsessed with understanding contributor pain points and behavior — goes through the product as a user, not just as a PM reviewing specs.
• Collaborative: builds trust with engineering, data science, operations, and sales — operates as a connector, not a gatekeeper.

Preferred Qualifications

• Experience owning an algorithmic content feed, recommendation system, or personalization engine as a PM — able to engage with ranking logic, signal weighting, and cold-start problems (strong preference, not hard requirement).
• Background at a high-scale consumer social platform, creator economy product, or content feed with large active user bases (strong preference, not hard requirement).
• Experience with creator identity, professional credentialing, or reputation systems.
• Background in AI/ML product development: worked on products where ML models are a core feature, not just a backend tool.
• 0-to-1 platform launches with demonstrated user growth.
• Experience with gig economy, crowdsourcing, or workforce platforms.
• Mandarin Chinese: significant practical advantage given our China-based engineering team.
• International/global product experience across multiple markets and languages.