Product Growth

OpenAI•San Francisco, CA

7d•$239,000 - $325,000•Onsite

About The Position

The Product Growth role is a hands-on generalist position focused on helping people derive lasting value from ChatGPT across international markets, use cases, and product experiences. The role partners with international and central teams to understand user needs, identify growth opportunities, and deliver measurable improvements across acquisition, activation, engagement, retention, and monetization. The role combines analytics and experimentation with product intuition, design judgment, and understanding of users and local markets. It uses AI-native automation and agentic tools to accelerate research, analysis, prototyping, and execution, while applying systems thinking across individual funnels and end-to-end workflows. The Growth team works across ChatGPT’s consumer and business segments worldwide, spanning acquisition, activation, retention, and monetization. The International Growth team works with regional leaders to identify market-specific user needs and product gaps, translate country priorities into product roadmaps and growth plans, and partner with cross-functional teams to test and ship improvements. It also develops shared capabilities such as segmentation, lifecycle journeys, and experimentation systems, measuring and adapting work for local markets and scaling successful approaches.

Requirements

Experience across product growth, growth strategy and operations, data science, experimentation, and growth design systems, including hands-on ownership of product experiments and measurable outcomes in a fast-moving technology company.
A user-first track record of translating research and behavior into product priorities and working with technical teams to ship improvements.
Deep expertise in funnel optimization and experimentation, including instrumentation, A/B testing, statistical power, holdouts, segmentation, cohort analysis, and interpreting incremental impact.
A track record of turning experiment results into sustained product improvements.
Ability to work across product and marketing levers, connecting audience and acquisition insights to activation, retention, and monetization.
Analytical fluency in funnel modeling and growth economics, including incrementality, LTV, CAC, and payback, and ability to move between strategic prioritization and hands-on execution.
Practical experience applying classifiers and propensity models to growth problems with Data Science and Engineering, including selecting useful signals, evaluating model quality, and testing targeted interventions.
Experience adapting products or growth programs across markets, with sound judgment about language, local behavior, business needs, and what should remain consistent globally.
Experience optimizing self-serve funnels and in-product upsell, cross-sell, or expansion journeys, or strong evidence of applying comparable growth expertise to a new customer segment or goal.
Ability to influence central and regional teams, work independently through ambiguity, and carry an initiative from diagnosis through execution and evaluation.

Nice To Haves

Experience scaling and continuously optimizing growth initiatives within Engineering and Data Science pods, from shared prioritization and implementation through experimentation and rollout.

Responsibilities

Partner with product, engineering, and design to turn insights into intuitive experiences and prototypes that improve how users discover value, complete tasks, and return.
Diagnose and optimize funnel performance using user research, event-level behavior, cohort analysis, and competitive insight; identify drop-offs and high-value segments, distinguish local needs from shared product friction, and prioritize interventions.
Build and use agentic workflows to automate research, analysis, prototyping, and experiment operations, with quality checks and human judgment where needed.
Connect acquisition and marketing insights to product journeys; partner with regional marketers and channel specialists on tests that improve qualified acquisition and activation.
Own an experimentation program across onboarding, activation, repeat usage, re-engagement, paid conversion, and expansion; partner with Engineering and Data Science on hypotheses, instrumentation, A/B tests and holdouts, readouts, staged rollouts, success metrics, and guardrails.
Build and execute an international growth roadmap covering in-product upsell, cross-sell, targeting, onboarding, activation and adoption, expansion, and monetization experiences.
Identify use cases, onboarding barriers, product entry points, and upgrade moments that can improve adoption and sustained customer value.
Partner with Data Science and Engineering to develop, deploy, and improve classifiers and propensity models for segmentation, targeting, and personalized in-product journeys; evaluate predictive quality and test incremental impact.
Own measurement across activation, retention, paid conversion, upsell, cross-sell, and revenue; separate incremental impact from market mix, seasonality, or cannibalization and use results to decide what to scale, adapt, or stop.
Run an operating cadence with regional and central partners, communicating international experimentation results, trade-offs, dependencies, and decisions.
Build reusable growth primitives, such as segmentation, lifecycle journeys, referral and expansion triggers, and experimentation tooling, for use across segments and markets.
Use AI-native workflows to accelerate research, prototyping, and iteration.