JOB DESCRIPTION 

Minimum qualifications:

• Bachelor's degree in an analytical/technical subject (e.g., Statistics, Computer Science, Engineering, Mathematics, or Economics) or equivalent practical experience.
   
• Experience developing and managing projects and collaborating with teams across geographies and functions.
   

Preferred qualifications:

• Experience with SQL-based database warehousing and dash boarding.
   
• Knowledge of commercial and emerging reporting tools and technologies (e.g., Tableau, QlikView, Microstrategy, Business Objects, Cognos, D3).
   
• Understanding of BI technologies and their application.
• Ability to work in a fast-paced, constantly evolving team environment and with statistical software such as Python and R.
   
• Interest and aptitude in data, metrics, analysis and trends, and applied knowledge of measurement, statistics, and program evaluation.
   
• Excellent problem solving skills, and in articulating product questions, pulling data from large datasets (e.g., SQL, BigQuery, etc.) and using statistics to arrive at an answer.
   

About the job

At Google, data drives all of our decision-making. Quantitative Analysts work all across the organization to help shape Google's business and technical strategies by processing, analyzing and interpreting huge data sets. Using analytical excellence and statistical methods, you mine through data to identify opportunities for Google and our clients to operate more efficiently, from enhancing advertising efficacy to network infrastructure optimization to studying user behavior. As an analyst, you do more than just crunch the numbers. You work with Engineers, Product Managers, Sales Associates and Marketing teams to adjust Google's practices according to your findings. Identifying the problem is only half the job; you also figure out the solution.

Responsibilities

• Prioritize and communicate user needs, make recommendations, and drive implementation for product or process changes. Identify and prioritize top challenges and key business growth opportunities.
• Work with leadership teams to implement tracking and reporting of metrics across global programs. Work with large data sets, automate data extraction, build monitoring/reporting dashboards and high-value, automated Business Intelligence solutions (data warehousing and visualization).
• Perform large-scale data analysis, statistical modeling, and inferential ML to identify opportunities for improvement and measure the impact of initiatives to make noticeable improvements based on impact and feedback.
• Design, develop, and establish Key Performance Indicators to monitor the health of database assets and the performance of internal operations, putting data models, and analytics in place that provide a platform for strategic decision-making.