Minimum qualifications:
- Bachelor's degree in Engineering, Math, Quantitative Science, or related technical field, or equivalent practical experience.
- 3 years of experience in statistical problem solving and analyzing data sets using SQL or comparable coding language (e.g. Python, R, Java, C++).
- 3 years of experience working in data analytics, consulting, data science, engineering, or a technical operations role.
Preferred qualifications:
- Master's degree in a quantitative field (e.g., Statistics, Computer Science, Engineering, Mathematics, Data Science, etc.).
- Experience in data analysis, with the ability to solve problems in complex, fast-moving, and ambiguous business environments.
- Knowledge of data warehousing concepts, including technical architectures, infrastructure components, ETL and reporting/analytics tools and environments.
- Ability to effectively communicate analysis and recommendations across a wide range of non-technical audiences.
- Ability to prioritize requests and work well in an environment with competing demands from multiple stakeholders.
- Ability to work cross-functionally with technical and business stakeholders with excellent listening, critical thinking, and problem-solving skills.
About the job
As a Marketing Analyst on the Ads Marketing Analytics team, you will drive measurement and analysis that supports global and high-value regional marketing programs. You will be innovative, analytical and an effective communicator whose insights enable marketers to develop valuable, highly effective programs. You will build, evaluate and enhance the data sets and pipelines that power our projects.You will lead design and implementation of reporting and dashboards to measure global Google marketing programs. You will prototype and iterate to provide insights at scale. In the course of this work you will be gathering data and system requirements, processing large data sets, performing ongoing analysis, and making presentations.Responsibilities
- Solve difficult, non-routine analysis problems, applying analytical methods / statistical models as needed. Integrate additional data sources into existing data sets and perform new, impactful calculations.
- Develop and maintain production implementations and use them to analyze large, complex data sets. Create and build dashboards to track metrics describing the quality of data produced by pipelines.
- Proactively identify quality issues, ensure they are visible to the appropriate stakeholders, and drive the resolution process. Prevent and mitigate technical debt by writing robust code or refactoring existing code with long term maintainability in mind.
- Execute quantitative business analysis on marketing activity performance metrics to generate insights and drive growth.
- Synthesize and present quantitative results to an executive audience of Sales, Marketing, Project Management and Engineering teams.
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