Description

Key Skills: SQL, Python, Data Analytics, Big Data, Statistical Analysis, A/B Testing, Data Visualization, ETL Pipelines, Predictive Modeling, Business Intelligence

Good to Have Skills: Mobile gaming analytics including retention curves, in-game economy, monetization, and LiveOps. Experience with Redshift, Athena, BigQuery, Hive or Spark, plus orchestration tools. Knowledge of Gen AI applications for boilerplate SQL, code review, and data exploration. Experience with experimentation platforms or feature stores. Background in consumer tech or mobile apps.

Roles & Responsibilities:

• Run in-depth analyses including funnel drop-offs, cohort behavior, segment deep-dives, and feature post-mortems to drive business decisions.
• Own retention and churn analysis by cohort, level, segment, and geography to build early prediction models for intervention strategies.
• Develop LTV and revenue forecasting models that are robust to seasonality, cohort mix, and content cadence for business planning.
• Manage game economy analysis including sources and sinks, currency inflation, reward-event systems, and bundle pricing elasticity.
• Analyze behavioral differences between paying and non-paying players to identify conversion moments and optimize pricing strategies.
• Design and analyze A/B tests with proper sizing, power analysis, guardrail metrics, and statistical integrity.
• Architect and optimize data pipelines connecting game telemetry, data warehouse, and ML systems while ensuring data quality.
• Present analysis findings to Product and Engineering leadership with clear narratives that can withstand executive scrutiny.
• Build self-serve dashboards and mentor team members to raise analytical capabilities across the organization.

Experience Required: 6-9 years in data analytics, preferably in gaming, consumer tech, or mobile applications.

Education: Bachelor's or Master's in Computer Science, Engineering, Statistics, Mathematics, or similar field

Key Skills

Education

Any Graduate