The central data science problem in Privacy Sandbox is quantifying the trade-offs between privacy and web business generation, so that we can ensure measurable progress in enhancing user privacy while also not taking away the business generation pathways that allow for a vibrant, open Internet, without content locked behind paywalls.
Requirements
- coding (e.g., Python, R, SQL)
- querying databases or statistical analysis
- Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field, or equivalent practical experience.
- 3 years of work experience using analytics to solve product or business problems
- Ph.D. or Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.
- 5 years of work experience using analytics to solve product or business problems
- applied knowledge of measurement, statistics, and program evaluation.
Responsibilities
- Leverage advanced statistical methods on massive, complex datasets to extract insights from billions of events and thousands of features across organizational sources.
- Develop and deploy automated solutions, ranging from SQL query automation to real-time Python classification and machine learning (ML) modeling, to address key tactical issues.
- Analyze intricate product and platform usage patterns, translating data-motivated insights into product strategy and engineering decisions.
- Demonstrate proficiency in technical and methodological conversations, as well as narrative-driven presentations.
- Develop an interest and aptitude for data, metrics, analysis, and trends, with applied knowledge of measurement, statistics, and program evaluation.
- Categorizing breakage on the web to ensure that privacy-sensitive users aren’t getting a broken browsing experience because of their privacy choices.
- Developing and validating new experimentation methodology that will work with the limited signals available in anonymized data.
Other
- Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field, or equivalent practical experience.
- 3 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a PhD degree.
- Ph.D. or Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.
- 5 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a PhD degree.
