Staff Analytics, Product & Marketing

About the role

EarnIn is looking for a Staff Analyst to work alongside our CMO and product leadership to scale user growth and engagement. You will design and implement AI-driven analytics workflows to automate decision-making while serving as a key contributor to our product and marketing strategy.

Key facts

What you'll do

• Partner with Engineering, Marketing, and Product teams to drive strategy across growth and product surfaces.
• Create AI-powered analytics agents to automate tasks like anomaly detection, funnel diagnostics, and business reporting.
• Collaborate with Engineering to move automated analytics systems into production.
• Build and manage frameworks for product analytics, experimentation, and causal measurement covering the full user lifecycle.
• Implement modeling and measurement strategies using uplift modeling and causal inference.
• Translate complex data and AI insights into clear narratives for both technical and non-technical stakeholders.

Requirements

• 7+ years of experience in data science or analytics with a focus on hands-on execution.
• Proficiency in Python, SQL, statistical modeling, and experimentation.
• Proven track record of building AI-driven workflows, including agents or LLM-based automation.
• Expertise in growth and product analytics, specifically regarding retention, monetization, activation, and engagement.
• Experience applying causal inference and uplift modeling.
• Ability to function as a high-impact individual contributor working directly with executive leadership.

Nice to have

• Background in consumer tech, fintech, or data-centric product companies.
• Familiarity with modern data stacks including Snowflake, Databricks, dbt, Looker, and Amplitude.
• Experience with Marketing Mix Modeling (MMM).

Skills & tools

• SQL
• Python
• Experimentation frameworks
• Causal inference
• AI/LLM agent development
• Statistical modeling

Practical notes

EarnIn participates in E-Verify. The company uses AI-powered tools during the hiring process for tasks such as interview transcription, scheduling, and resume review, though all final hiring decisions are made by humans. Candidates may opt out of interview recording without impacting their application status.