In this role, you will be working with multiple stakeholders across Play to define metrics and deliver insightful data and analysis. You will serve as an analytics expert for the partners, using numbers to help them make decisions. You will drive better product and business decisions to improve Play business generation. You will be responsible for translating data into interpretations and recommendations and implement process improvements. You will serve as a key input in product development and operations decision-making. You will work collaboratively across Play teams (e.g., Engineering, Program Management, User Experience (UX) and Commercial Operations) as well as other product teams and cross-functional teams such as Legal, Finance and Marketing teams.Google Play offers music, movies, books, apps and games for devices, powered by the cloud. It syncs across devices and on the web. As part of the Android and Mobile team, Googlers working on Google Play do everything from engineering our backend systems, to shaping product strategy, to forming great content partnerships. They make it possible for people to do things like buy an ebook or song on their Android phone, then have it instantly available on their laptop. The Google Play team enhances the Android ecosystem by giving developers and partners a premium store where they can reach millions of users.
Responsibilities
- Drive analysis for Play, focusing on product features and user experience across Play business generation, with the primary goal of optimizing the purchase flow and experience.
- Partner with Program Management, Engineering team, and other Play teams to provide data feed, experiment design and product insights that will improve performance, and ensure proper logging and metrics are available for performance measurement.
- Act as thought partner to produce insights and metrics for various technical and business stakeholders across Play.
- Deliver presentations of findings and recommendations to multiple levels of leadership, creating visual displays of quantitative information.
- Develop framework and build views to measure product success and provide insights at scale.
Qualifications
Minimum qualifications:
- Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
- 8 years of experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL) or 5 years of experience with a Master's degree.
Preferred qualifications:
- Master's degree in Statistics, Mathematics, Data Science , Engineering, Physics, Economics, or a related quantitative field.
- Experience with developing machine learning models (e.g., supervised and unsupervised), launch experiments (e.g., A/B Testing), and end-to-end data infrastructure and analytics pipelines.
- Experience in identifying opportunities for business/product improvement and defining/measuring the success of those initiatives.
- Experience in developing new models, methods, analysis and approaches.
- Experience with classification and regression, prediction and inferential tasks, training/validation criteria for Machine Learning (ML) algorithm performance.
- Knowledge of business generation.