ABOUT EARNIN

As one of the first pioneers of earned wage access, our passion at EarnIn is building products that deliver real-time financial flexibility for people living paycheck to paycheck. Our community members access their earnings as they earn them, with options to spend, save, and grow their money without mandatory fees, interest rates, or credit checks. We’re fortunate to have an incredibly experienced leadership team, combined with world-class funding partners like A16Z, Matrix Partners, DST, Ribbit Capital, and a very healthy core business with a tremendous runway. We’re growing fast and excited to bring on world-class talent to help shape the next chapter of our growth journey.

EarnIn is becoming an AI-native company, embedding AI agents into how we build, analyze, and operate across every function. Teams use AI Agents to move from ideas to execution faster. By letting agents handle repetitive tasks, our people can focus on judgment, creativity, and hard problems. We pair this experimentation with the strict review and security guardrails our regulated financial environment requires, always keeping a focus on privacy and the people who rely on our products.

As a company, we are becoming AI-native, and we encourage you to use AI tools throughout much of your interview process. If you use AI during the live interview, just say so; a quick, natural mention of how it helped and why you are using it is all we need. What we're evaluating is your judgment, reasoning, and ability to own and defend your work, not whether AI was involved. Some rounds, particularly those focused on your career history and past experiences, will not allow the use of AI, and we'll let you know of those in advance. When in doubt, ask your recruiter or interviewer directly.

POSITION SUMMARY

We are seeking a Staff Analyst to partner closely with 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.

The Mountain View base salary range for this full-time position is $215,000 to $263,000, plus equity and benefits. Our salary ranges are determined by role, level, and location. This is a hybrid position in Mountain View, requiring in-office work 2 days a week.

WHAT YOU'LL DO

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.

WHAT WE'RE LOOKING FOR

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).