What To Do
- Take ownership of your models, guiding them from initial research to full deployment in production, and ensuring they continue to deliver value over time.
- Build and improve models to predict customer revenue and lifetime value (LTV) for mobile apps, helping our customers make better business decisions.
- Providing benchmarks for customer metrics, including Install-to-Trial conversions, Install-to-Paid conversions, and LTV compared to industry standards.
- Make A/B testing smarter by developing tools that identify winning strategies faster and with less data.
- Create models that design highly effective paywalls tailored to each app’s category and audience, optimizing pricing, layout, and content.
- Use data to uncover actionable insights, such as identifying where a small price adjustment could significantly boost revenue.
Requirements
- Strong Analytical Foundation: You have a solid grasp of math, statistics, and probability theory.
- Machine Learning Expertise: You know how to build both interpretable and advanced black-box machine learning models, and you’ve put them into production before.
- Revenue-Focused Experience: You’ve worked on predictive models for metrics like revenue and LTV, and you understand the challenges in these areas.
- End-to-End Ownership: You’re comfortable taking a model from an idea to a live, production-ready system—and keeping it running smoothly.
- Product-based Approach: You focus on results that make a difference for users, driving value with every project you take on.