Senior Data Analyst – UA Growth (Remote, Equity)

Midwest Startups; United States; Remote; USD 120,000 - 180,000; Full time

Benefits offered by this job

Remote-first

Equity plan

Bonuses

Bonusly recognition

Open PTO

Job summary

Mode.Inc is seeking a Senior Data Analyst to partner with our User Acquisition team. You’ll own measurement of user acquisition across our mobile apps and web properties, from attribution to cohort LTV and payback, delivering clear recommendations on where to spend the next dollar.

The ideal candidate brings exceptional analytical skills, strong SQL and Python, and deep familiarity with mobile marketing data.

Qualifications

• 4+ years in analytics, with at least 2 years supporting user acquisition or performance marketing for mobile apps.
• Strong SQL and Python programming skills, and experience with large-scale production data.
• Business acumen to translate data and analysis into business impact.
• Exceptional written and verbal communication skills for cross-functional collaboration.

Responsibilities

• Design, build, and maintain datasets and data pipelines to enable data-driven decisions across the org.
• Improve data quality, accuracy, and documentation for self-service analytics.
• Own UA performance measurement across paid channels (e.g., Meta, Google, TikTok, AppLovin, Unity).
• Build and maintain predictive LTV models and cohort curves for bidding and budgeting decisions.
• Reconcile data across MMPs, ad networks, and internal events; investigate attribution discrepancies.
• Analyze web-to-app funnel from landing page to install to engagement; identify drop-offs.
• Design and read incrementality tests and A/B tests to measure true lift beyond last-touch attribution.

Skills

SQL

Python

Analytics

Communication

Tools

AppsFlyer

Adjust

Singular

Branch

Redshift

Spark

Airflow

Job description

Mode.Inc is seeking a Senior Data Analyst to partner with our User Acquisition team. You’ll own measurement of user acquisition across our mobile apps and web properties, from attribution to cohort LTV and payback, delivering clear recommendations on where to spend the next dollar.

The ideal candidate brings exceptional analytical skills, strong SQL and Python, and deep familiarity with mobile marketing data.