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OpenAI's GTM Intelligence Solutions team is seeking a Data Scientist to build decision systems that empower customer-facing teams with actionable intelligence. This role combines hands-on technical depth with strong product and business judgment to create the next generation of go-to-market intelligence.
You will own a flexible portfolio of high-impact decision data products, working closely with Technical Success and GTM teams. Your responsibilities include setting roadmap and methodology for GTM intelligence systems, building canonical feature datasets across product telemetry, commercial systems, CRM data, and field activity, and choosing appropriate approaches (heuristics, statistical models, ranking, or machine learning) based on decision requirements and data maturity.
Key responsibilities:
- Define and build intelligence systems that help customer-facing teams prioritize accounts, identify risks and opportunities, and measure outcomes
- Own the full lifecycle of intelligence products: feature definition, methodology, evaluation, SQL/Python pipelines, monitoring, and versioning
- Partner closely with Technical Success stakeholders to understand workflows, test assumptions, and shape solutions
- Define exposure, action, feedback, and outcome data needed to evaluate and continuously improve products
- Create monitoring for data quality, freshness, system behavior, and adoption
- Ship and operate reliable first versions, partnering with Analytics Engineering and Data Engineering for shared infrastructure
You should have significant experience shipping and operating model-backed or rules-based decision products in production (not just analyses). You're exceptional in SQL and strong in production Python, comfortable moving from source data through production decision products independently. You can define problems, challenge assumptions, propose methodology, and establish evaluation standards. You measure success through reliable adoption and better decisions, not model sophistication.
Required qualifications include significant applied Data Science or related quantitative role experience with direct ownership of production decision systems, advanced SQL and strong production Python, demonstrated success taking models from prototype to monitored production, and strong stakeholder discovery and communication skills.
Preferred experience includes Databricks, Spark, dbt, Airflow, modern cloud warehouses, B2B SaaS and usage-based products, CRM/Salesforce data, model and feature versioning, and familiarity with agentic systems.
