Data Scientist, SMB Ads Growth

About the Role

OpenAI's ads platform is experiencing rapid global scale. As the Lead Data Scientist for SMB Ads Growth, you will architect the analytics function end-to-end—driving strategy across targeting, funnel optimization, and performance forecasting. You will work directly with the SMB Ads Marketing team and your insights will be the primary catalyst for high-stakes decisions across marketing, product, and sales engineering.

What You'll Do

Full-Funnel Analytics

• Establish the foundational growth metrics and North Star KPIs for the SMB Ads ecosystem, optimizing the journey from lead acquisition to long-term retention.

• Diagnose funnel friction points through advanced behavioral analysis and quantify the incremental revenue impact of proposed optimizations.

• Partner cross-functionally to transform complex data findings into actionable, high-priority roadmaps for product and marketing stakeholders.

Targeting, Segmentation & Propensity Modeling

• Engineer sophisticated propensity models and look-alike frameworks to identify and capture high-LTV SMB advertisers.

• Own the lifecycle of target list construction, including advanced data enrichment, multi-dimensional prioritization, and granular performance tracking.

• Develop robust segmentation architectures that power hyper-personalized outreach across paid, partnership, and outsourced (BPO) channels.

• Synthesize market signals to refine our value proposition, ensuring OpenAI remains a key platform for SMB business growth.

Campaign Analytics & Measurement

• Design and implement rigorous multi-touch attribution and incrementality frameworks to evaluate channel efficacy.

• Lead the experimental roadmap: formulate hypotheses, execute A/B and multivariate tests, and communicate results to executive leadership.

• Automate business-critical reporting and dashboards to provide real-time visibility during weekly operating reviews.

Forecasting & Planning

• Build high-fidelity revenue and advertiser growth models to project performance against quarterly and annual targets.

• Simulate the impact of various growth levers—such as regional expansion and channel activation—to drive strategic resource allocation.

• 5+ years of experience in data science or growth analytics within an ads platform, marketplace, or high-growth B2B environment.

• Proven track record of deploying machine learning models (propensity, LTV) that significantly moved business metrics.

• Strong SQL; proficient in Python or R.

• Experience thriving in ambiguous "0-to-1" environments, with a hands-on approach to building data infrastructure and processes.

• Prior experience at a major scaled ads platform (e.g., Meta, Google, LinkedIn).

• Experience working in 0-1 environments

• A deep passion for artificial intelligence and proficiency in leveraging AI tools to accelerate modeling and insight generation.