Cloud Security Product Data Scientist
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Minimum qualifications:
- Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
- 8 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL) or 5 years work experience with an advanced degree.
Preferred qualifications:
- Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
- 8 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL).
About the job
As a Cloud Security Product Data Scientist, you will works within the strategy and operations group to equip Google security business leaders with the data and insights you need to confidently make decisions that improve our business and products. You will apply our data engineering, data science and data analysis skills to build trusted data sets, analyses, metrics and dashboards that are tailored to the priorities and products of the Cloud security business. You will focus on scalable, executive-level and portfolio-wide insights and work closely with other functional (e.g., sales, marketing, finance, etc.) and product specific analytic teams who offer additional complementary views for users.
The US base salary range for this full-time position is $156,000-$229,000 + 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.Responsibilities
- Partner with product, engineering, GTM, and post sales leadership, to identify and answer critical, strategic questions through data analysis.
- Conduct analyses and experiments to understand user behavior, identify trends, and uncover opportunities for product improvement and growth.
- Apply statistical methods and modeling techniques to extract insights and build predictive models.
- Develop and monitor core metrics and dashboards to track product performance, user engagement, and business outcomes. Communicate complex problem-solving findings and recommendations clearly and concisely to both technical and non-technical audiences.
- Design, develop and maintain data pipelines that aggregate and enrich key product and business data to power analyses and dashboards. Ensure data quality and problem-solving in all outputs.
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