Head of Growth (App)

Role Overview We are seeking a metrics-obsessed operator to own the full-funnel expansion of our mobile application environment. As the Head of Growth (App), you will be directly accountable for active app MAU, retention curves, user activation, and premium subscription conversions. You will maintain a direct integration line into the App Product team to unify feature engineering with rigorous growth loops. Key Responsibilities & Core Problems to Solve

• Build Conversion Funnels: Establish an efficient web-to-app infrastructure that successfully migrates Patrika's high-volume, unowned web traffic into logged-in, highly trackable app users.
• Solve the Retention Challenge: Redesign user journeys to move away from low-duration "drive-by" visit behaviors, cementing the app as a home for habitual, daily interaction.
• App Store Discovery Optimization: Drive strategic App Store Optimization (ASO) and user acquisition architectures to compete effectively against premium news application offerings from major regional competitors.
• Continuous Experimentation: Conduct continuous, small-scale onboarding, push notification, and pricing tests to steadily improve CAC and LTV economics.

Experience & Scale Requirements

• Must have led the growth engine of a consumer app with several million MAU featuring a live subscription or paywall business model.
• Complete mastery over full-funnel analytics, including onboarding drop-offs, D1/D7/D30 retention analytics, and trial-to-paid conversion metrics.
• Practical familiarity operating within price-sensitive, low-ARPU emerging markets dominated by payment friction (such as UPI-dependent behaviors).

Critical Disqualifiers

• Growth expertise limited to paid-acquisition-heavy categories (such as gaming or fintech) that bypass structural retention and long-term habit-loop design.
• No direct exposure to subscription or premium paywall models (having only scaled free, fully ad-supported applications).
• Inability to address technical Indian Android ecosystem realities, such as optimizing for low-RAM performance, minimizing app download sizes, and navigating data constraints.