Data Scientist III, Research, Privacy Sandbox
Google
Full-time
On-site
Minimum qualifications:
- 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.
Preferred qualifications:
- 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.
About the job
The Privacy Sandbox Data Science team supports Privacy Sandbox by ensuring user's activity private across a free and open Internet. 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. Anticipated projects include, 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.The US base salary range for this full-time position is $141,000-$202,000 + 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
- 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.