Data Scientist III, Product, Consent and Transparency

1 Month ago • 5-6 Years • Data Analyst • $132,000 PA - $189,000 PA

Job Summary

Job Description

This Data Scientist III role within Google's Trust Analytics team focuses on providing quantitative support and strategic insights related to user consent, transparency, and data privacy. Responsibilities include performing data analysis using SQL, R, and Python; gathering, cleaning, and validating data from various sources; reporting KPIs to leadership; translating analysis into actionable business insights; influencing product development decisions; and building scalable analytical solutions. The role requires expertise in statistical analysis, data mining, and project management, within the context of Google's large-scale data infrastructure and compliance requirements. The team works on high-stakes challenges surrounding data privacy regulations and AI, scaling consent and transparency across Google's ecosystem.
Must have:
  • Master's degree in quantitative field
  • 5+ years experience in statistical data analysis
  • SQL, R, Python proficiency
  • Data mining & querying expertise
  • Project management experience
Good to have:
  • 3 years experience in scripting and statistical analysis (R, Stata, SPSS, SAS)
  • Experience in a complex organization
  • Developing and managing metrics
  • Program/product evaluation experience
Perks:
  • Bonus
  • Equity
  • Benefits

Job Details


Minimum qualifications:

  • Master's degree in Statistics, Economics, Engineering, Mathematics, a related quantitative field, or equivalent practical experience.
  • 5 years of experience with statistical data analysis, data mining, and querying (e.g., SQL).
  • 1 year of experience managing analytical projects.

Preferred qualifications:

  • 3 years of experience in scripting, statistical analysis (e.g., R, Stata, SPSS, SAS), developing and managing metrics, and evaluating programs/products.
  • 1 year of experience working in a complex, matrixed organization.

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.

The Trust Analytics team is part of the larger Trust team which is responsible for building durable solutions that enable products across Google to easily provide coherent, compliant, and age-appropriate experiences that empower users to make meaningful and informed choices about their data. The Trust team is very data-driven and works on some of the most pressing, high stakes challenges that Google is faced with when responding to regulatory-driven efforts, including those concerning AI, and also helps scale consent, transparency, controls across the Google ecosystem.

The US base salary range for this full-time position is $132,000-$189,000 + 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 .

Responsibilities

  • Perform analysis by utilizing relevant tools (e.g., SQL, R, Python). Using comprehensive technical knowledge, use custom data infrastructure or existing data models.
  • Own the process of gathering, extracting, and compiling data across sources via relevant tools (e.g., SQL, R, Python). Format, re-structure, and validate data to ensure quality.
  • Report Key Performance Indicators (KPIs) to support business reviews with cross-functional/organizational leadership team. Translate analysis results to business insights or product improvement opportunities.
  • Provide analytical insights and recommendations to influence product feature development decisions, and with some guidance.
  • Build and prototype analysis and business cases iteratively to provide insights at scale. Develop comprehensive knowledge of Google data structures and metrics.

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