GCP Lifecycle Analytics Lead

• Lead analytics strategy for GCP Lifestyle Growth Marketing, collaborating closely with cross-functional leadership across Strategy and Operations, Product, and Marketing to build performance measurement methods, integrate multiple data sources, and generate actionable business insight.
• Demonstrate technical leadership in data extraction and manipulation by delivering user-friendly, informative dashboards and recurring reports, continually iterating and prototyping these visualizations to meet business needs.
• Provide advanced analytics and experimentation support to enable data-driven marketing, applying sophisticated statistical techniques and data mining to rapidly solve complex business problems.
• Support the rigorous design and implementation of A/B and multivariate hypothesis tests, leveraging causal inference methods as appropriate to ensure statistically significant results.
• Provide high-level insight and detailed, segmented, investigative analyses to identify key opportunities to deeply understand and enhance customer utilization of Google Cloud products and overall market expansion.

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 1P and 3P martech systems, integration points for data, building Extract Transform Load (ETL) pipelines.
• Experience architecting scalable dashboards and reporting suites, statistically sound measurement frameworks.
• 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.
• Familiarity with B2B, Product-Led Growth (PLG), or growth marketing data and acquisition funnels.

The Google Cloud team helps customers transform and evolve their business through the use of Google’s global network, web-scale data centers, and software infrastructure. Growth Marketing is a vital growth engine for Google Cloud, driving customer acquisition, product adoption, and revenue expansion across our self serve and enterprise funnels. In the current environment, where scaling our business, optimizing conversion pathways, and driving measurable impact are more important than ever, growth marketing strategy and experimentation are top-of-mind priorities for leadership. As the Analytics Lead for Google Cloud Platform (GCP) Lifecycle Analytics, you will be at the forefront of full-funnel measurement, experimentation, and reporting of the effectiveness of growth marketing initiatives, lifecycle programs, and expansion opportunities. In this role, you will work with marketing, sales, product, engineering, strategy & operations, and data science peers to own and conduct in-depth data analysis to inform strategic growth and investment decisions.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $180000 - $261000 (USD) + 20% bonus target + equity + benefits

Learn more about benefits at Google.Applicants in San Francisco: Qualified applications with arrest or conviction records will be considered for employment in accordance with the San Francisco Fair Chance Ordinance for Employers and the California Fair Chance Act.Note: By applying to this position you will have an opportunity to share your preferred working location from the following: New York, NY, USA; Austin, TX, USA; Kirkland, WA, USA; Seattle, WA, USA; San Francisco, CA, USA; Sunnyvale, CA, USA.

• 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.