Key Responsibilities:
- Track and analyze the performance of user acquisition (UA) campaigns across GEOs, platforms, and ad networks using mobile attribution tools (AppsFlyer, Adjust, Firebase, SKAdNetwork,Appslovin etc).
- Analyze gameplay telemetry and player behavior to uncover patterns and opportunities for product improvement.
- Build, maintain, and automate dashboards and reports for UA/Product metrics: CPI, ROAS, LTV, retention, payback periods,Churn,User engagement etc.
- Partner with UA & creative teams to evaluate creative variants, run incrementality tests, and analyze cohorts (view-through vs click-through, retention cohorts).
- Develop predictive models to forecast campaign outcomes, optimize budget allocation, and estimate LTV / ROAS across different spends or channel mixes.
- Conduct rigorous statistical analyses-including A/B testing, cohort analysis, regression modeling, and significance testing-to derive actionable insights.
- Set up and refine ETL pipelines to pull raw campaign / attribution / MMP / in-app data into warehouses (BigQuery or similar) for analysis.
Qualifications:
- Bachelor's degree in a quantitative discipline (Statistics, Data Science, Computer Science, or related fields).
- 4 - 6 years in data analysis, with a strong emphasis on predictive modeling, statistical analysis, and UA/growth analytics, ideally within gaming or mobile apps.
- Proficient in experiment design, significance testing, cohort analysis, regression modeling, and predictive forecasting.
- Strong skills in SQL (querying raw data) and experience in Python or R for aggregation, predictive modeling, automation, and statistical analysis.
- Hands-on with attribution tools (AppsFlyer / Adjust / Firebase / SKAdNetwork) and comfortable interpreting metrics like ROAS, CPI, LTV, retention.
- Proficiency in dashboarding / visualization tools (Tableau, Power BI, Looker, or similar).
- Excellent communication skills: ability to explain analytical findings and make recommendations to non-technical stakeholders.
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