Sr. PRODUCT MANAGER - PLATFORM GROWTH & SCALING

Centific

6d•$160,000 - $180,000•Remote

About The Position

Centific is seeking a technically fluent Sr. Product Manager to lead the growth and scaling of its OneForma platform. This role involves a 0-to-1 platform reinvention, transforming OneForma from a transactional crowd platform into a professional creator network. The initial six months will focus on stabilizing the platform by redesigning the contributor onboarding experience and addressing legacy technical debt. Following this, the focus will shift to designing and building a social-marketplace hybrid, including algorithmic task feeds, contributor identity profiles, gamified engagement loops, and viral referral mechanics. The goal is to scale the contributor base from 1.8 million to 18 million and enhance the data quality behind AI models used globally. This is a fully remote, full-time position with a salary range of $160K–$180K plus bonus, reporting to the AVP, Product Management.

Requirements

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
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
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

Nice To Haves

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

Responsibilities

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
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
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