Minimum qualifications:

• Bachelor's degree in a quantitative field (e.g., Statistics, Computer Science, Engineering, Mathematics, Data Science, etc.) or equivalent practical experience.
• 9 years of experience as a data analyst or data scientist using statistical techniques and quantitative modeling.
• 7 years of experience analyzing data sets using SQL.
• Experience developing data visualizations.

Preferred qualifications:

• Experience collaborating with cross-functional stakeholders to drive consensus on technical data requirements, including strategic data direction, ad-hoc analysis, or development of new data pipelines.
• Experience working with first and third-party martech systems, integration points for data, building Extract Transform Load (ETL) pipelines.
• Experience presenting complex data analyses as easy to understand insights to leadership, with the ability to represent and influence discussions involving quantitative concepts and data-based stories.
• Experience architecting scalable dashboards and reporting suites, statistically sound measurement frameworks.
• Familiarity with Business-to-Business and Partner marketing data.

About the job

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.

Responsibilities

• Guide partner marketing analytics strategy, collaborating with cross-functional and executive leadership to establish performance measurement frameworking and business reporting.
• Integrate complex, multi-source data to build user-friendly dashboards and recurring reports, providing high-level insights and segmented, investigative analyses that drive key business decisions.
• Uncover actionable insights that expose operational opportunities, directly informing strategic changes to enhance customer usage and engagement across Google Cloud products.
• Apply statistical methods to solve complex business problems, supporting the end-to-end design and implementation of A/B, multivariate, and causal inference testing.
• Serve as a technical authority in end-to-end data extraction, complex manipulation, interactive data visualization, and advanced data mining techniques.