Business Data Scientist, Subscriptions and Consumer Infrastructure, Marketing (English, Spanish)

Google's leadership team hand-picks thorny business challenges, and members of BizOps work in small teams to find solutions. As part of this team you fully immerse yourself in data collection, draw insight from analysis, and then zoom out to develop compelling, synthesized recommendations. Taking strategy one step further, you also persuasively communicate your recommendations to senior-level executives, roll-up your sleeves to help drive implementation and check back-in to see the impact of your recommendations.

Google Marketing starts with technology and ends with the user, bringing them together unconventionally. We approach marketing by demonstrating how our products solve problems, from the everyday to the epic, changing the game, redefining the medium, prioritizing the user, and letting the products speak for themselves.

The Subscriptions and Customer Growth Marketing organization drives consumer apps and subscription growth. We partner with product engineering and insights to understand the user and bring helpful products to market.

Responsibilities

• Conduct analysis of user and subscriber behavior, identify trends, and uncover insights that drive product improvements and marketing strategies.
• Create clear and informative reports and dashboards to track key usage metrics and communicate findings to stakeholders.
• Collaborate with cross-functional teams to design and implement A/B tests to evaluate the impact of product changes on business outcomes.
• Build models to predict user churn, identify at-risk subscribers, and forecast future user trends.
• Work closely with product managers, marketers, and engineers to translate data insights into actionable recommendations.

Minimum qualifications:

• Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience.
  
• 3 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a relevant PhD degree.
  
• Ability to communicate in English and Spanish fluently to interact with local stakeholders.

Preferred qualifications:

• PhD in a quantitative field such as Statistics, Economics, Engineering, Mathematics, a related quantitative field, or equivalent practical experience.
• 3 years of experience in data science or product analytics, with a track record of driving user growth in consumer facing products or services.
• Experience with statistical data analysis such as generalized linear models, multivariate analysis, clustering/segmentation and sampling methods, controlled experiment design, and causal inference methods.
• Experience with R or Python for statistical analysis and data visualization.