Data Scientist, Growth Analytics

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.

Your Background:

• 4+ years of experience in Analytics, Data Science, Decision Science, or Growth Analytics, with demonstrated impact in a high-growth B2C technology company. (streaming, gaming, fintech, or consumer app businesses preferred).
• Deep expertise in SQL, including complex query optimization, dimensional modeling, and large-scale analytical data warehouses such as Databricks, Snowflake, BigQuery, or Redshift.
• Strong programming experience in Python for statistical modeling, automation, experimentation, AI applications, and production-quality analytics workflows.
• Experience building AI-powered analytical tools, agentic workflows, or LLM-based applications that automate repetitive analysis, accelerate decision-making, or improve business operations.
• Proven experience building predictive models and applying machine learning techniques to solve business problems in marketing, growth, or customer lifecycle optimization.
• Deep understanding of experimentation methodologies, including A/B testing, causal inference, Bayesian statistics, incrementality testing, and observational analysis.
• Experience developing executive-facing dashboards and scalable self-service analytics solutions using Tableau, Preset, or similar BI platforms.
• Demonstrated ability to influence cross-functional strategy and communicate complex analytical concepts to executive and non-technical audiences.
• Strong curiosity, autonomy, and passion for building scalable analytics capabilities and establishing best practices that raise the bar across the organization.
• Familiarity with modern AI frameworks and tooling (e.g., LangChain, LangGraph, OpenAI APIs, MCP, vector databases, or similar agent orchestration frameworks) is highly desirable.
• Strong understanding of digital marketing measurement, attribution methodologies, media performance, and customer acquisition economics is a plus.

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