Description Crazy Labs is one of the world’s leading mobile game developers and publishers, specializing in hyper-casual, hybrid, and casual spaces. With over 7 billion downloads, we have a deep understanding of what it takes to transform promising game ideas into profitable hits. We’re seeking a Growth Analytics Team Lead with expertise in marketing and ad monetization to spearhead a team dedicated to optimizing business performance through data-driven insights. This role centers on analyzing user acquisition, ad revenue, and player engagement to drive growth and refine monetization strategies. Key Team Responsibilities: Data Analysis & Insights: Analyze marketing, user acquisition, and ad monetization data to identify trends and optimize strategies. Performance Tracking: Develop standardized dashboards and real-time reports to monitor key KPIs and support decision-making. Campaign Optimization: Support A/B testing, attribution modeling, and budget allocation to maximize efficiency and ROAS. Creatives & UA Analysis: Identify high-performing channels, campaigns, and creatives to refine ad monetization and acquisition strategies. Ad Monetization Growth: Collaborate with the Ad Monetization team to track, visualize, and optimize revenue performance. Cross-Team Collaboration: Work closely with Game Analysts, R&D, and Product teams to enhance engagement and monetization strategies. Statistical Modeling & Forecasting: Utilize SQL, Python, or R to predict growth opportunities and optimize marketing performance. Requirements Experience: 3-5 years in marketing (user acquisition) analytics within mobile gaming. Having experience leading a team is a plus. Technical Skills: Strong proficiency in SQL & Python Marketing & Monetization Expertise: Understanding of UA channels, ad mediation, and key metrics like LTV, ARPU, and eCPM. Analytical Mindset: Ability to run statistical analyses, forecast trends, and generate actionable insights. Collaboration: Strong communication skills to work with cross-functional teams and optimize data-driven strategies #J-18808-Ljbffr