Head of Growth & Marketing Analytics

EarnIn•Mountain View, CA

1d•$215,000 - $263,000•Hybrid

About The Position

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 Growth & Marketing Analytics Lead 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. This person will also drive the transformation of analytics with AI-driven workflows. The ideal candidate combines strategic thinking with a hands-on approach, diving into data regularly, while also setting the broader vision. 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.

Requirements

10+ years of experience in analytics, with at least 2 years in a people management role.
Strong technical skills in SQL, Python, data visualization tools (Amplitude, Tableau) and experimentation.
Has direct experience in marketing analytics using Media Mix Models (MMM), difference-in-differences and other causal inference techniques.
Proven track record of leading high-performing marketing or product analytics teams.
Excellent communication and storytelling skills.
Ability to balance strategic thinking with hands-on execution.

Nice To Haves

Experience in fintech, consumer tech, or a data-driven product organization.
Familiarity with modern data stacks (e.g., Databricks, Tableau, Amplitude).
Experience influencing executive stakeholders and driving cross-functional initiatives.

Responsibilities

Team Leadership & Mentorship Hire, lead, coach, and develop a high-performing team of product and marketing analysts.
Foster a culture of curiosity, analytical rigor, and continuous learning.
Define clear goals, priorities, and growth paths for the analytics team. Start by managing a team of 2–3 direct reports, with the opportunity to grow the team as the business scales
Analytics Strategy & Execution Own the company’s marketing measurement, experimentation, and insight generation for paid, owned, and integrated channels, and for performance across acquisition, activation, engagement, retention, and LTV
Lead the evolution of Media Mix Modeling (MMM) and causal inference frameworks to measure both performance and brand impact.
Partner with the Growth team to optimize owned channels (SEO, Referrals) onboarding funnels, and lifecycle marketing to drive engagement.
Build AI-driven workflows to automate recurring analytics (e.g., business reviews, anomaly detection, and insight generation), significantly reducing manual analysis and accelerating decision-making.
Partner with Analytics Engineering to ensure scalable and reliable data models and pipelines.
Hands-On Analysis Perform deep-dive analyses to uncover insights that inform product and business decisions.
Collaborate with data engineering and product teams to improve data pipelines and instrumentation.
Cross-Functional Collaboration Act as a strategic thought partner to identify opportunities, measure success, and optimize Marketing and product performance.
Communicate complex analytical findings clearly and effectively to non-technical audiences and influence action.
Improve marketing efficiency (CAC/LTV) through better measurement and insights
Increase user growth and retention leveraging owned channels.
Establish scalable analytics systems that reduce manual analytics