Job Description

Minimum qualifications:

• Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field, or equivalent practical experience.
• 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.
• Experience in experimental design, A/B testing analysis, and applying causal inference methods.
• Experience partnering with executive technical and non-technical stakeholders.

Preferred qualifications:

• Master’s degree in Statistics, Machine Learning, Data Science, Economics, or a related quantitative field.
• 5 years of experience developing supervised and unsupervised models (classification, regression, prediction) and implementing training/validation criteria for ML performance.
• Experience in engagement domain.
• Experience in online App Store ecosystems or digital marketplaces.

About the job

As part of the Platform and Devices team, You will work on Google Play to shape the product strategy, engineer our backend systems, and form content partnerships. You make it possible for people to do things like buy a game or app on the Android phone, then have it instantly available across all the form factors.

We work on a variety of challenging data science projects to drive product and go-to-market decisions for Play. Our direction is to Power Play’s growth by building an understanding of our users and developers, enabling data-driven decision making, through insights, thought leadership, and unified data foundations.

You will contribute to strategy, data science and analytics, while facilitating alignment through excellent communication. Our team partners with the leadership to run important functions that integrate our existing organizations and deliver projects. We help Engineers, Product Managers, UX, and other cross-functional stakeholders to build amazing products that delight our users and developers facilitating delivery and adoption.

As a Data Scientist for the Play Apps team, you will be the Insights based driver for product strategy and business growth. You will partner with Play stakeholders (Engineering, Product Management, UX, and Commercial Operations) and cross-functional teams (Finance, Marketing) to define metrics and deliver data analysis. Your primary mission is to translate data into recommendations, directly influencing product development, launch strategies, and operational decisions to boost Apps Engagement. Additionally, you will advocate process improvements within the analytics workflow.

The US base salary range for this full-time position is $163,000-$237,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at GoogleThe US base salary range for this full-time position is $163,000-$237,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google

Responsibilities

• Partner with Engineering, Product Management, and other Play or Apps leadership to inform strategy, influence with insights, and provide methodological excellence, insights, and metrics that reduce risk and improve user experience.
• Design and analyze A/B experiments, develop and operationalize novel measurement methodologies, including ensuring proper logging and metrics, to quantify user behavior, engagement, and user value for app features.
• Conduct post-launch and longitudinal analyses to identify growth opportunities, understand the impact, and inform future product development.
• Research, develop, and monitor the ML models to improve user engagement, including establishing evaluation criteria.
• Follow engineering best practices to create data pipelines, automate reports, and iteratively build prototypes to provide insights, solving complex analytical needs.