The opportunity
The GTM Data Science team partners with Go-to-Market, Technical Success, Product, Engineering, RevOps, and Strategic Finance to build the shared intelligence layer for OpenAI's B2B business. The team turns product usage, customer behavior, revenue, field activity, and customer…
What you'll do
Build a unified GTM intelligence layer that connects product telemetry,: customer health, revenue, support tier, lifecycle stage, field activity, and qualitative feedback.
Turn adoption breadth, usage depth, sentiment, and customer maturity signals: into next-best-action systems for Technical Success and field teams.
Create a measurement foundation for Technical Success playbooks, including: whether recommended actions were taken and whether they improved customer outcomes.
Help OpenAI understand customer happy paths: the use cases, product behaviors, and interventions that lead to durable adoption, expansion, and retention.
Productize insights into workflows used by Technical Success, Sales, RevOps,: Finance, Product, and executive leadership.
Define and lead the roadmap for GTM Intelligence and Technical Success: insight products in partnership with cross-functional leaders.
What they're looking for
- Build the data science foundation for Technical Success, including core: metrics, customer health definitions, intervention measurement, and reusable playbook analytics.
- Develop propensity score models for model and product feature adoption,: helping Technical Success and GTM identify which customers are most likely to adopt, which interventions can move adoption, and where support should focus.
- Build, mentor, and lead a small team of data scientists and cross-functional: analytics partners as the GTM Intelligence function scales.
- Set technical standards for modeling, metrics, experimentation,: documentation, and production readiness across the team's work.
