Business Intelligence Analyst, Growth Marketing

Minimum qualifications:

• Bachelor's degree in a research or quantitative field (e.g., Social Sciences, Statistics, Mathematics, Bioinformatics, Economics, etc.) or equivalent practical experience.
• 3 years of experience in analyzing data using statistical and quantitative modeling.
• 3 years of experience translating business problems into research questions and translating research findings and insights into marketing recommendations.
• 3 years of experience analyzing data sets using SQL.
• Experience managing research and measurement agencies.

Preferred qualifications:

• Master's degree in a quantitative field (e.g., Statistics, Computer Science, Engineering, Mathematics, Data Science, etc.).
• 3 years of experience creating A/B tests, multivariate hypothesis tests, including experimental design and analysis.
• Experience collaborating with cross-functional stakeholders to drive consensus on requirements, including strategic direction, ad-hoc analysis, or development of new data pipelines.
• Experience presenting to leadership, with the ability to represent and influence discussions involving quantitative concepts and data-based stories.
• Experience building Extract Transform Load (ETL) pipelines.
• Experience with marketing or product analytics data.

About the job:

As a Business Intelligence Analyst on the Google Cloud Growth Marketing team, you will be at the forefront of identifying and resolving marketing issues and opportunities. Our Growth Marketing Analysts are the analytics experts across various marketing channels and programs.

In this role, you will work with Engineering, Marketing, and Sales to conduct data-oriented analysis to inform the strategic marketing direction. You will support the design and implementation of marketing campaigns, including A/B testing, to support the growth of and harvest learnings for Google Cloud marketing channels. Your suite of deliverables include building and analyzing metrics that can be leveraged for business performance measurement, experimentation (A/B testing, multivariate testing), causal inference, and derive insights about behavior. You will bring data to life through compelling narratives.

Know the user. Know the magic. Connect the two. At its core, marketing at Google starts with technology and ends with the user, bringing both together in unconventional ways. Our job is to demonstrate how Google's products solve the world's problems--from the everyday to the epic, from the mundane to the monumental. And we approach marketing in a way that only Google can--changing the game, redefining the medium, making the user the priority, and ultimately, letting the technology speak for itself.

The US base salary range for this full-time position is $114,000-$163,000 + 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.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

Responsibilities:

• Collaborate with cross-functional stakeholders to complete analysis, integrate multiple data sources, and generate business insight.
• Deliver user-friendly and informative dashboards and recurring reports, iterate and prototype to meet business needs.
• Provide advanced analytics and experimentation support, enabling data-driven marketing by applying statistical techniques to solve business problems.
• Support the design and implementation of A/B testing, multivariate hypothesis tests, and leverage causal inference methods as appropriate.
• Demonstrate subject matter expertise and technical leadership in data extraction and manipulation, dash-boards, visualization, and analytical/statistical/data mining techniques.