Google's Go-to-Market Operations (GTM) team needs to analyze and synthesize product feedback to identify actionable insights that drive product improvements and Go-To-Market strategies for Google's Ads business, ensuring growth and effective operations.
Requirements
- 3 years of experience in statistical problem-solving and analyzing data sets using SQL or comparable coding.
- Experience in data analysis, with the ability to solve problems in a changing, and ambiguous business environment through data intuition and business acumen.
- Java or Python for data processes
- SQL and statistical methods for data analysis
- Data models and visualizations
- Statistical and potentially machine learning techniques
Responsibilities
- Design and implement data processes using Java or Python to collect, clean, transform, and analyze product feedback data from various sources.
- Conduct advanced quantitative data analysis using SQL and statistical methods to identify significant trends, correlations, and root causes within product feedback.
- Develop sophisticated data models and visualizations to communicate feedback insights in a clear and compelling manner to technical and non-technical audiences.
- Collaborate with data scientists to apply statistical and potentially machine learning techniques to uncover deeper patterns and predict future user needs based on feedback.
- Partner with product managers and GTM teams to translate data-driven insights into actionable recommendations for product development and go-to-market strategies.
Other
- Master's degree in Engineering, Math, Quantitative Science, or a related technical field, or equivalent practical experience.
- 3 years of experience working in data analytics, consulting, data science, engineering, or a technical operations role.
- 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.
- Advocate for a data-driven approach to understanding user sentiment
