Own a data and AI driven analytics stack that informs product and growth decisions, partnering with execs and cross‑functional teams to turn measurement into scalable AI powered workflows.

Own AI driven analytics workflows and productionize them with engineering to support activation, engagement, retention, and monetization.
Develop measurement and causal frameworks across paid, owned, and product surfaces to guide experiments and uplift modeling.
Communicate insights to both technical and non‑technical audiences to influence roadmaps and growth levers.

Job Description

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.

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.

Preferred

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

Benefits

EarnIn

4.5 Glassdoor

EarnIn lets you access your money as you earn it — not days or weeks later.We’re reimagining the way money moves to make financial momentum accessible to everyone. That starts with payday every day and builds with tools like credit monitoring, automated savings accounts, and low-balance protection. All with no interest, no credit checks, and no mandatory fees. So our customers have as many options as possible to save and spend on their terms.EarnIn’s pioneering Earned Wage Access app is backed by world-class partners like A16Z, Matrix Partners, and DST. Since our founding in 2013, 3.8 million customers have given it over 380,000 5-star reviews for helping them access over $15 billion in earnings. That means:- 49% can now cover an unexpected expense of $400 since using EarnIn- 73% can budget more effectively with EarnIn- 66% have been able to pay bills on time with EarnIn’s helpWe’re proud of that impact. Because no one should feel stuck — held back from their ambitions, their life — simply because they can’t access the money they’ve already earned. That’s why EarnIn is here, to help people move forward with the lives they want today and the goals they have for tomorrow.Join us.EarnIn is a financial technology company, not a bank. The Deposit Account, Secured Account, and EarnIn Card are issued by Evolve Bank & Trust, Member FDIC. The EarnIn Card is issued pursuant to a license from Visa USA Inc.

Founded in 2012

Mountain View, California, USA

560 employees (41 in marketing)

earnIn.com

87% recommend to a friend

92% CEO approval

Traffic Signals

Monthly Visitors

1.5M

Monthly Google Ads Budget

$365.2K

Traffic Source Mix

28.4%

Direct

56.9%

Referral

8.7%

Social

1.9%

Paid

Headcount Trend

Current headcount: ~562

Marketing Team

Marketing Team Size

26 (5% of company)

Funding

Total Funding

$415.1M

Last Raise

$150M

Debt Financing, 6 months ago

Funding History

Sep 2025
Debt Financing • $150M
Sep 2025
Debt Financing • $75M
Dec 2018
Series C • $125M

Recent News

EarnIn adds B2B option as consumer groups attack EWA

Oct 31, 2025 • American Banker

A New Era of Payday: Real-Time Wages Are Here – sponsored by EarnIn

Oct 24, 2025 • WCNC

Why Are Earned Wage Access Companies Like EarnIn Moving Into Payroll?

Oct 22, 2025 • Forbes

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.

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.

Preferred

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