About the job
About Our Team
At OpenAI, our Financial Engineering (FinEng) team plays a pivotal role in shaping the financial landscape of our products, including pricing strategies, packaging, checkout processes, payment systems, and subscription models. We collaborate closely with Product, Engineering, Risk, Finance, and Go-to-Market teams to ensure that the payment experience for OpenAI products is seamless, reliable, and efficient on a global scale.
About This Position
As a Data Scientist within the FinEng team, you will take ownership of analytics and experimentation initiatives aimed at enhancing our checkout and payment systems, subscriptions, and pricing & monetization strategies. Your responsibilities will include defining key performance metrics, building robust data assets, and designing experiments that drive conversion rates, minimize churn and payment failures, and broaden our global payment options. Your contributions will have a direct impact on revenue, customer satisfaction, and our international scaling efforts.
This position is located in San Francisco, CA, and operates under a hybrid work model requiring three days in the office each week. We also provide relocation assistance for new hires.
Your Responsibilities
Lead analytics and experimentation for checkout and payment systems across different methods and regions, focusing on improving conversion while managing risk and latency.
Develop and implement an experimentation framework for our in-house checkout process, defining success metrics, executing staged rollouts, and applying offline incrementality for scenarios where online testing is not practical.
Create operational transparency and establish source-of-truth data in partnership with the FinEng Data Engineering team, develop team-level metrics, SLAs, and self-service dashboards that promote proactive decision-making.
Drive analytics for subscription, retention, and monetization strategies, ensure readiness for new subscription feature launches, reduce involuntary churn through targeted retrials and nudges, and create frameworks to optimize pricing strategies based on elasticity and foreign exchange considerations.
Ideal Candidate Profile
Minimum of 5 years of experience in a quantitative role (data science, product analytics, or experimentation) within dynamic or fintech environments.
Proficient in SQL and Python, with demonstrated experience in designing and interpreting A/B tests and quasi-experimental designs.
Skilled in developing product metrics from the ground up and operationalizing them for effective decision-making.
Strong communication skills, capable of effectively engaging with Product Managers, Engineers, Risk and Finance partners, and executive leadership.
