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OpenAI is seeking a Data Scientist to lead the analytics function for its SMB Ads platform, which is experiencing rapid global scale. You will architect end-to-end analytics strategy, driving insights across targeting, funnel optimization, and performance forecasting. Your work will directly influence high-stakes decisions across marketing, product, and sales engineering teams.
Key responsibilities include establishing foundational growth metrics and North Star KPIs for the SMB Ads ecosystem, optimizing the customer journey from lead acquisition through long-term retention. You will diagnose funnel friction points through advanced behavioral analysis, quantify incremental revenue impact of proposed optimizations, and partner cross-functionally to translate complex data findings into actionable roadmaps.
You will engineer sophisticated propensity models and look-alike frameworks to identify high-LTV SMB advertisers, own the full lifecycle of target list construction including data enrichment and multi-dimensional prioritization, and develop segmentation architectures powering hyper-personalized outreach across paid, partnership, and outsourced channels.
Campaign analytics responsibilities include designing rigorous multi-touch attribution and incrementality frameworks, leading the experimental roadmap with A/B and multivariate testing, and automating business-critical reporting and dashboards for real-time visibility during weekly operating reviews.
You will build high-fidelity revenue and advertiser growth models to project performance against quarterly and annual targets, and simulate the impact of various growth levers such as regional expansion and channel activation to drive strategic resource allocation.
Required: 5+ years in data science or growth analytics within ads platforms, marketplaces, or high-growth B2B environments. Proven track record deploying machine learning models (propensity, LTV) that significantly moved business metrics. Strong SQL proficiency and fluency in Python or R. Experience thriving in ambiguous 0-to-1 environments with hands-on data infrastructure building.
Strongly preferred: Prior experience at major scaled ads platforms (Meta, Google, LinkedIn), 0-to-1 environment experience, and deep passion for AI with proficiency leveraging AI tools to accelerate modeling and insight generation.
