Data Analyst

User Acquisition Data Analyst (Mobile Gaming)

About the Opportunity:

Key Responsibilities:

• Own recurring user acquisition (UA) reporting, including:
  • Daily performance monitoring.
  • Weekly performance reviews.
  • Budget pacing reports.
  • Monthly executive reporting.
• Analyze key performance metrics including cost, CPI, installs, retention, revenue, and ROAS across channels, platforms, and geographies.
• Translate data into actionable recommendations regarding channel performance, media mix, and optimization opportunities.
• Partner with User Acquisition and Finance teams to develop forecasting models for CPI, paid installs, and budget utilization.
• Conduct ad hoc analyses to support campaign and creative optimization efforts.
• Perform statistical significance testing on key marketing metrics such as CTR, CVR, IPM, and ROAS.
• Monitor and maintain data quality across attribution platforms, analytics tools, and reporting systems.
• Troubleshoot dashboard, reporting automation, and attribution-related issues.
• Collaborate with data and platform teams to ensure reporting accuracy and pipeline health.
• Develop and enhance dashboards, reporting solutions, and data models as business needs evolve.

Required Qualifications:

• 3-5 years of experience in marketing analytics, business intelligence, or data science supporting mobile user acquisition campaigns.
• Advanced SQL skills, preferably with experience working in BigQuery environments.
• Strong experience creating dashboards and visualizations using Tableau, Looker Studio, Mixpanel, or similar BI tools.
• Deep understanding of mobile marketing attribution, measurement platforms (MMPs), SKAdNetwork (SKAN), and app store reporting.
• Experience analyzing mobile user acquisition performance and communicating insights to marketing, finance, and executive stakeholders.
• Ability to work independently in a fast-paced, data-driven environment with minimal onboarding.

Preferred Qualifications:

• Experience in mobile gaming analytics.
• Knowledge of hybrid monetization models, including in-app purchases (IAP) and in-app advertising (IAA).
• Proficiency with Python or R for statistical analysis and process automation.
• Experience designing and evaluating A/B tests, geo-lift studies, or incrementality experiments.
• Familiarity with data reconciliation across multiple attribution and reporting sources.
• Strong understanding of mobile user behavior and growth marketing strategies.

Desired Skills:

• Advanced analytical and problem-solving abilities.
• Strong communication and presentation skills.
• Forecasting and modeling expertise.
• Attention to detail and data accuracy.
• Ability to translate complex data into business recommendations.
• Experience working with cross-functional stakeholders.