Product Data Analyst, TapBlaze

Product Data Analyst, TapBlaze

Company TapBlaze
Job title Product Data Analyst (Gaming)
Job location Los Angeles, CA, USA
Type Full Time

Responsibilities:

  • KPI Monitoring: Report on these KPIs, identifying trends, and areas for improvement, and providing actionable recommendations
  • Data Analysis: Extract insights and trends related to player behavior, game performance, and in-game economy
  • A/B Testing: Design and implement A/B tests, formulating clear hypotheses and conducting statistical significance testing
  • Dashboards and Reporting: Develop and maintain reporting dashboards and automated reports to provide real-time visibility into game performance
  • Predictive Modeling: Build and maintain predictive models using statistical and machine learning techniques for forecasting player retention, churn, and spending behavior
  • Data Integrity: Ensure data accuracy and integrity, troubleshoot data issues, and collaborate with engineering for improved data collection processes. Regularly review and update data governance policies.
  • Market Analysis: Conduct a comprehensive market analysis to understand industry trends and competitive positioning. Inform strategic decisions based on market insights.
  • User Feedback Analysis: Analyze user feedback and support tickets to identify common issues or feature requests, contributing to game improvements.

Requirements & Skills:

  • Ability to effectively balance the needs of technology, business, and player experience
  • Understanding of economy and monetization design
  • Plays F2P mobile games
  • Continuously looking for ways to improve and iterate on existing framework, or building anew for best results
  • Great attention to detail – actually has read this job description; please include the phrase “beauty is in the details” in your cover letter.
  • Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, or a related field
  • Strong proficiency in SQL, Python, R, or similar data analysis tools
  • Experience with data visualization tools (e.g., Tableau, Power BI)
  • Knowledge of statistical modeling and machine learning techniques

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