Job description

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 those with the unique needs of 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 are excited to continue bringing world-class talent onboard to help shape the next chapter of our growth journey. 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). 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. 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 #LI-Hybrid At EarnIn, we believe that the best way to build a financial system that works for everyday people is by hiring a team that represents our diverse community. Our team is diverse not only in background and experience but also in perspective. We celebrate our diversity and strive to create a culture of belonging. EarnIn does not unlawfully discriminate based on race, color, religion, sex (including pregnancy, childbirth, breastfeeding, or related medical conditions), gender identity, gender expression, national origin, ancestry, citizenship, age, physical or mental disability, legally protected medical condition, family care status, military or veteran status, marital status, registered domestic partner status, sexual orientation, genetic information, or any other basis protected by local, state, or federal laws. EarnIn is an E-Verify participant. EarnIn does not accept unsolicited resumes from individual recruiters or third-party recruiting agencies in response to job postings. No fee will be paid to third parties who submit unsolicited candidates directly to our hiring managers or HR team.

Requirements

Must-haves

Collaborate with Product, Engineering, Marketing, and cross‑functional partners to inform, influence, and execute strategy across product and growth surfaces.
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.
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

Application prep

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Platform: greenhouse
Effort: quick

Benefits

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