B2B Growth Data Scientist: Measurement & Experimentation

OpenAI

San Francisco (CA)

Vor Ort

USD 140.000 - 220.000

Vollzeit

14 Tage+

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Zusammenfassung

OpenAI is seeking a Data Scientist to lead measurement, experimentation, and decision science for B2B marketing demand generation. You will partner with Marketing, Sales, RevOps, Finance, Product, and Engineering to connect activity to qualified pipeline and revenue, while building AI-native measurement workflows.

The role focuses on defining north-star metrics, running randomized tests, lift studies, and causal analyses to optimize campaign impact across channels and audiences, with a long-term

Qualifikationen

  • Quantitative expertise in measurement, experimentation, and marketing analytics for B2B demand generation.
  • Strong fluency with SQL/Python to join marketing platform, web analytics, CRM, and revenue data.
  • Experience translating analyses into marketing decisions and optimization strategies.

Aufgaben

  • Define metrics for B2B demand generation and pipeline impact.
  • Design and run measurement experiments across channels and campaigns.
  • Analyze performance by channel, audience, campaign, and account segments.
  • Collaborate with Marketing, Sales, RevOps, Finance, Product, and Engineering to improve data instrumentation and data quality.
  • Build AI-native measurement and decision-support workflows using LLMs and agents.

Kenntnisse

SQL
Python
Experimentation
Causal inference
Marketing analytics
Communication
Cross-functional collaboration
Action bias

Tools

LLMs
AI tools
CRM systems
Web analytics
A/B testing platforms

Jobbeschreibung

OpenAI is seeking a Data Scientist to lead measurement, experimentation, and decision science for B2B marketing demand generation. You will partner with Marketing, Sales, RevOps, Finance, Product, and Engineering to connect activity to qualified pipeline and revenue, while building AI-native measurement workflows.

The role focuses on defining north-star metrics, running randomized tests, lift studies, and causal analyses to optimize campaign impact across channels and audiences, with a long-term

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