Staff Analytics, Product & Marketing

EarnIn•Mountain View, CA

20h•$215,000 - $263,000•Hybrid

About The Position

We are seeking a Staff Analyst to partner closely with the CMO and product leadership to drive user growth and engagement. This leader will shape and drive the analytics strategy, mentor and develop the team, and collaborate cross-functionally with Marketing, Product, and Engineering to translate business needs into actionable insights. The primary goal of this position is to architect and build agentic workflows that transform how analytics operates: design AI-driven pipelines that work autonomously, surface insights proactively, and scale decision-making across the organization. You bring both the strategic vision to see where automation unlocks the most value, and the hands-on depth to get into the data and build it yourself.

Requirements

7+ years in analytics, data science with deep hands‑on execution.
Strong technical skills in SQL, Python, experimentation, and statistical modeling.
Experience building AI‑driven analytics workflows (LLMs, agents, automation, or similar).
Solid background in product and growth analytics across activation, engagement, retention, and monetization.
Experience with causal inference, uplift modeling, and experimentation frameworks.
Ability to operate as a high‑leverage IC who partners closely with executives and cross‑functional leaders.
Excellent communication and storytelling skills for technical and non‑technical audiences.

Nice To Haves

Experience in fintech, consumer tech, or data‑driven product organizations is a plus.
Familiarity with modern data stacks (Databricks, Snowflake, dbt, Amplitude, Looker) is a plus

Responsibilities

Collaborate with Product, Engineering, Marketing, and cross‑functional partners to inform, influence, and execute strategy across product and growth surfaces.
Build AI‑driven analytics agents that automate workflows such as experimentation readouts, funnel diagnostics, anomaly detection, and business reviews, and partner with Engineering to productionize these systems at scale.
Develop and maintain experimentation, causal measurement, and product analytics frameworks that support acquisition, activation, engagement, retention, monetization, and LTV.
Design and implement measurement and modeling approaches across paid, owned, and product surfaces, using uplift modeling, causal inference, and experimentation rigor (MMM optional).
Develop a deep understanding of complex product and marketing systems to identify opportunities, risks, and levers for growth.
Communicate insights clearly to technical and non‑technical audiences, influencing product and marketing roadmaps through data, modeling, and AI‑driven insights.