Product Data Scientist, Reliability Analytics

Join Google as a Product Data Scientist in Reliability Analytics

Minimum Qualifications:

• Master's degree in Statistics, Economics, Engineering, Mathematics, or a related quantitative field, or equivalent practical experience.
• At least 3 years of relevant experience in analytics, solving product or business problems, coding in Python, R, SQL, querying databases, or conducting statistical analysis.
• A minimum of 1 year of experience in managing analytical projects.

Preferred Qualifications:

• 5 years of experience using analytics to solve product or business issues, proficient in coding (Python, R, SQL), querying databases, and statistical analysis.

About the role:

As a Product Data Scientist for Google Cloud's Reliability Analytics team, you will help advance our mission to support Google's expansive user base. Our Data Scientists supply quantitative insights, foster market understanding, and apply a strategic eye to support our partners across the organization. In this role, you will act as an analytics expert for your partners, helping them make well-informed decisions using data. You'll craft narratives filled with meaningful insights derived from data, make critical recommendations to our engineers and product managers, and enjoy the challenge of quantifying data one moment and presenting your findings the next.

At Google Cloud, we’re enhancing every organization’s ability to undergo digital transformations through our advanced, enterprise-grade solutions leveraging cutting-edge technology. With tools designed to help developers build sustainably, our solutions are trusted by customers across more than 200 countries and territories to foster growth and tackle their most pressing business challenges.

Your responsibilities will include:

• Collaborating closely with stakeholders on cross-project and team initiatives to pinpoint and refine key business or product questions.
• Translating business inquiries into manageable analyses, defining evaluation metrics, or conceptualizing mathematical models.
• Utilizing custom data infrastructures or existing models as needed, with a focus on designing and evaluating models to mathematically address and resolve issues with limited precedents.
• Leading the process of data gathering, extraction, and compilation from multiple sources using tools such as SQL, R, and Python; ensuring data quality and readiness for analysis.

If you're driven by data and looking to impact a leading team within a major tech company, apply to Google's Product Data Scientist, Reliability Analytics role today and propel your career into the future.