Minimum qualifications:
- Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, a related quantitative field, or equivalent practical experience.
- 7 years of experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL) or experience with an advanced degree.
- 3 years of experience as a people manager within a technical leadership role.
- 12 years of experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL).
- 4 years of experience as a people manager within a technical leadership role.
Want more jobs like this?
Get jobs in Bangalore, India delivered to your inbox every week.
About the job
Help serve Google's worldwide user base of more than a billion people. Data Scientists provide quantitative support, market understanding and a strategic perspective to our partners throughout the organization. As a data-loving member of the team, you serve as an analytics expert for your partners, using numbers to help them make better decisions. You will weave stories with meaningful insight from data. You'll make critical recommendations for your fellow Googlers in Engineering and Product Management. You relish tallying up the numbers one minute and communicating your findings to a team leader the next.
Google is an engineering company at heart. We hire people with a broad set of technical skills who are ready to take on some of technology's greatest challenges and make an impact on users around the world. At Google, engineers not only revolutionize search, they routinely work on scalability and storage solutions, large-scale applications and entirely new platforms for developers around the world. From Google Ads to Chrome, Android to YouTube, social to local, Google engineers are changing the world one technological achievement after another.
Responsibilities
- Perform analysis utilizing relevant tools (e.g., SQL, R, Python). Provide thought leadership through strategic contributions (e.g., suggests new analyses, experiments to drive improvements in the business).
- Develop quantitative models and frameworks to assess the business opportunity associated with improvements in attribution, incrementality testing, full-funnel measurement, Online-to-Offline (O2O) measurement.
- Quantify the impact of data deprecation and regulatory changes on Ads performance. Develop metrics to track the effectiveness of our mitigation strategies and data durability initiatives.
- Define success metrics for our efforts to create a unified measurement platform. Analyze the impact of closing measurement gaps and enhancing the customer value proposition.
- Monitor and analyze competitive offerings, identifying opportunities and threats. Develop metrics to track our competitive positioning and the effectiveness of our response to market dynamics.