Data Scientist

About the Role:

We are looking for a problem solver who thrives at the intersection of data science, growth strategy, and AI-powered automation.  You’ll focus on diving deep into data, creating scalable data solutions, building agentic AI workflows, supporting growth marketing measurement, and enabling growth experimentation to power smarter decision-making for growth marketing. This is a highly technical and data-intensive role ideal for someone who is passionate about applying advanced analytics and AI to drive business impact in a fast-paced environment.

This is a hybrid role based out of our San Francisco or Los Angeles office. You must be willing to travel to the office two days/week. Please note that we do not provide relocation assistance for this role.

What You'll Do:

• Lead the design and evolution of measurement frameworks that quantify marketing effectiveness across the full customer lifecycle, including acquisition, activation, retention, and brand impact.
• Create business intelligence suites that provide a holistic view of marketing performance across growth marketing, brand marketing, Search/Answer Engine Optimization (SEO/AEO), Customer Relationship Management (CRM), social, content, partnerships, and business development, spanning both performance and brand health metrics. 
• Build scalable analytics products that provide executive visibility into marketing performance across paid, owned, and earned channels.
• Design and implement agentic AI solutions that automate recurring analyses, generate actionable insights, orchestrate multi-step analytical workflows, and accelerate decision-making for growth marketing, brand marketing, SEO/AEO, CRM, social, and broader marketing operations teams.
• Leverage large language models (LLMs), AI agents, and modern AI frameworks to improve productivity, automate reporting, enhance experimentation workflows, and surface intelligent recommendations.
• Evaluate and implement advanced statistical techniques - including Bayesian modeling, causal inference, uplift modeling, and media mix modeling - to improve marketing measurement and optimization.
• Drive the organization's experimentation strategy by designing rigorous A/B tests, incrementality studies, geo experiments, and causal inference methodologies to measure both short-term performance and long-term business impact. 
• Partner closely with Data Engineering to design robust data models, improve data quality, and define scalable pipelines that support analytics at scale.
• Build and maintain dashboards and self-service analytics solutions in Preset, Databricks, or Tableau that empower growth marketing, brand marketing, SEO/AEO, CRM, social, and cross-functional partners with timely, actionable insights.