Applied Data Science & Insights Leader – GTM Intelligence Solutions and Technical Success

Role Overview

The Applied Data Science & Insights Lead for GTM Intelligence Solutions and Technical Success will be a hands-on technical leader responsible for shaping how OpenAI measures, understands, and improves customer adoption across our B2B products. This role will build the data science foundation for Technical Success: defining the metrics, models, operating insights, and decision systems that help the team scale customer adoption and expansion with rigor.

What You Will Do

Build AI/ML-powered intelligence products that connect account health, product usage, customer lifecycle, support tier, qualitative sentiment, commercial context, and field actions into a practical operating system for GTM and Technical Success. 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.

Why It Might Be a Fit

10+ years of experience in applied data science, analytics, machine learning, quantitative strategy, or a closely related field. Deep technical skill in SQL and Python, with the ability to move from raw tables to production-quality models, metrics, and decision systems.

Requirements

• 10+ years of experience in applied data science, analytics, machine learning, quantitative strategy, or a closely related field
• Deep technical skill in SQL and Python
• Strong applied experience with statistical modeling, causal inference, machine learning, customer segmentation, churn or health modeling, or recommendation systems
• Experience with propensity score modeling, uplift modeling, or related causal methods for adoption, activation, retention, or product feature usage
• Experience building production or workflow-embedded data products for GTM, sales, customer success, technical success, growth, or enterprise SaaS teams
• Product intuition and business judgment for turning ambiguous questions into repeatable models, tools, metrics, and operating cadences
• Excellent communication skills, including the ability to distill complex analysis into clear recommendations for technical partners, field teams, and executives
• Comfort partnering across technical and non-technical teams, including Product, Engineering, Technical Success, Sales, RevOps, Finance, and Data Engineering
• A track record of operating autonomously in fast-moving environments and raising the quality of how teams use data to make decisions
• Experience leading teams or serving as a technical lead for multi-person data science initiatives, including mentoring, roadmap-setting, and quality review
• Ability to hire, develop, and retain strong data science talent while creating a collaborative, high-accountability team culture
• An advanced degree in a quantitative field, or equivalent practical experience

Benefits

• Relocation assistance
• Hybrid work model
• Equal opportunity employer
• Affirmative Action and Equal Employment Opportunity Policy Statement
• Background checks for applicants
• Reasonable accommodations for applicants with disabilities