Senior Monetization Data Analyst

Inclusively Remote; United States; Remote; USD 110,000 - 160,000; Full time

Benefits offered by this job

Remote-first

Equity plan

Bonuses

Wellness days

Bonusly recognition

PTO & holidays

Job summary

Mode is a fast-growing tech company building AI, data, mobile apps, and digital experiences with a 100M+ monthly active user footprint. We seek a Senior Data Analyst to partner with Monetization, owning revenue metrics and pricing experiments across mobile apps and web properties.

You’ll design data pipelines, improve data quality, and develop LTV models to drive pricing, packaging, and revenue mix decisions. Strong SQL/Python and subscription analytics are essential.

Qualifications

• Analytical excellence to dissect complex, ambiguous problems and uncover actionable insights.
• Solid SQL and Python programming skills, and experience working with large-scale production data.
• Business acumen to translate data and analysis into business impact.
• Exceptional written and verbal communication skills to collaborate across teams.

Responsibilities

• Design, build, and maintain datasets and data pipelines for self-service analytics.
• Improve data quality, accuracy, reliability, and documentation.
• Own revenue and monetization metrics across the portfolio (ARPU, LTV, churn).
• Design and analyze pricing, packaging, and paywall experiments with statistical rigor.
• Build subscription cohort and LTV models to inform pricing decisions.
• Analyze ad monetization performance and balance with retention.

Skills

SQL

Python

Data analysis

LTV modeling

AB testing

Tools

Looker/LookML

Redshift

Airflow

Tableau

Job description

Mode is a fast-growing tech company building AI, data, mobile apps, and digital experiences with a 100M+ monthly active user footprint. We seek a Senior Data Analyst to partner with Monetization, owning revenue metrics and pricing experiments across mobile apps and web properties.

You’ll design data pipelines, improve data quality, and develop LTV models to drive pricing, packaging, and revenue mix decisions. Strong SQL/Python and subscription analytics are essential.