Description

Join our team and be a key driver of our machine learning and data science initiatives. You will own the entire lifecycle of your models, from initial research to production deployment and ongoing optimization, directly impacting our customers' success.

What You Will Do

• Own the end-to-end lifecycle of your machine learning models, from research and development to deployment and continuous improvement in production.
• Build and refine models to accurately predict customer revenue and lifetime value (LTV) for mobile apps, empowering our customers to make data-driven business decisions.
• Develop benchmarks for critical customer metrics, including Install-to-Trial conversions, Install-to-Paid conversions, and LTV, providing valuable context against industry standards.
• Enhance our A/B testing capabilities by creating intelligent tools that accelerate the identification of winning strategies with greater efficiency.
• Develop sophisticated models to design highly effective and personalized paywalls, optimizing pricing, layout, and content based on app category and audience.
• Leverage data analysis to uncover actionable insights, such as identifying pricing adjustments with significant revenue potential.

What We Expect

• Strong Analytical Foundation: A solid understanding of mathematics, statistics, and probability theory.
• Proven Machine Learning Expertise: Experience building and deploying both interpretable and advanced machine learning models into production environments.
• Revenue-Focused Experience: Prior experience working on predictive models for revenue and lifetime value (LTV) and a strong understanding of the associated challenges.
• End-to-End Ownership Mentality: Comfort and experience taking models from ideation to production deployment and ensuring their ongoing reliability and performance.
• Product-Driven Approach: A focus on delivering tangible results and driving value for users through your machine learning projects.

Note: If you feel strongly that you have what it takes for this role but don’t check 100% of the boxes—that’s okay—we encourage you to apply anyway and highlight what you can bring to the table.