We are looking for a Lead Mobile Analytics professional to drive the strategy, architecture, and execution of analytics across our mobile ecosystem. In this role, you will partner closely with Product, Growth, Marketing, Engineering, and Data teams to unlock insights that shape product strategy and accelerate user and revenue growth.
You will lead the development of a world-class mobile analytics framework, enabling deep understanding of user behavior, experimentation at scale, and predictive insights such as pLTV (predictive Lifetime Value). Your work will directly influence product roadmap decisions, acquisition strategy, monetization models, and long-term user engagement.
This role requires a combination of product thinking, statistical rigor, technical depth, and leadership to build scalable analytics solutions and mentor a high-performing analytics team.
What You Will Do
Drive Mobile Analytics Strategy
- Own the mobile analytics vision and roadmap, ensuring alignment with product growth and business objectives.
- Design scalable measurement frameworks for mobile acquisition, activation, retention, engagement, and monetization.
- Establish best practices for mobile data instrumentation, experimentation, and analytics governance.
Deliver Deep Product Insights
- Lead analysis of mobile user behavior, funnels, and lifecycle metrics to identify opportunities for product improvements.
- Translate complex datasets into clear insights that drive product decisions and measurable growth.
- Partner with product leaders to shape data-informed product strategies.
Lead Experimentation and Decision Science
- Build and scale A/B testing and experimentation frameworks across mobile products.
- Apply advanced statistical methods and causal inference techniques to evaluate product and growth initiatives.
- Champion a culture of experimentation and evidence-based decision making across teams.
Predictive Analytics and pLTV Models
- Implementation of predictive Lifetime Value (pLTV) models to optimize acquisition and monetization strategies.
- Use advanced analytics and modeling to forecast user retention, revenue, and long-term engagement.
- Partner with growth teams to allocate marketing investments using ROI and predicted user value.
Own the Mobile Data Ecosystem
- Ensure reliable, scalable mobile event tracking and analytics infrastructure across platforms.
- Work with large-scale datasets using SQL, BigQuery, Databricks, and modern data platforms.
- Leverage Python and advanced analytics techniques for modeling, automation, and experimentation analysis.
- Collaborate with engineering teams to ensure high-quality data pipelines and instrumentation frameworks.
Lead Mobile Attribution and Growth Measurement
- Own measurement and attribution across mobile marketing channels using AppsFlyer or similar attribution platforms.
- Evaluate and optimize performance across paid acquisition, organic growth, and re-engagement campaigns.
- Connect marketing performance with long-term user value and product engagement metrics.
Build and Lead a High-Impact Analytics Team
- Hire, mentor, and develop a high-performing team of product and mobile analysts.
- Elevate analytics capabilities across the organization through best practices, tooling, and knowledge sharing. Influence executive decision-making through clear storytelling with data.