Data Scientist III, Product, Pixel @ Google
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Job Details
Minimum Qualifications
Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics or equivalent practical experience.
5 years of experience with analysis applications (e.g., extracting insights, performing statistical analysis, or solving business problems) and coding (e.g., Python, R, SQL) or 2 years with a Master's degree.
Preferred Qualifications
Master's degree in the related quantitative field and 5 years of work experience with analysis applications and coding (Python, R, SQL).
About the Job
Help serve Google's worldwide user base of over a billion people. As a member of the Data Scientist III, Product, Pixel team, you provide quantitative support, strategic market insights, and analytics expertise to drive better decision-making in both Engineering and Product Management.
You will:
- Weave stories with meaningful insights from data.
- Make critical recommendations for product and engineering teams.
- Work on scalability solutions, large-scale applications, and innovative platforms.
Responsibilities
The successful candidate will:
- Perform analysis using tools like SQL, R, and Python.
- Gather, extract, compile, re-structure, and validate data from multiple sources.
- Report KPIs to support business reviews with leadership.
- Translate analysis into business insights and product improvement opportunities.
- Own the Pixel dashboard workstream including data engineering and dashboard design.
- Build and prototype analysis and business cases using Google data structures and metrics.
Compensation
The US base salary range for this full-time position is $132,000-$189,000 + bonus + equity + benefits. Additional details regarding salary, bonus, equity, and benefits will be provided during the hiring process.
Key skills/competency
Data Analysis, SQL, Python, R, Statistical Analysis, Dashboard Design, Data Engineering, Business Insights, KPI Reporting, Data Visualization
How to Get Hired at Google
🎯 Tips for Getting Hired
- Customize your resume: Highlight analytics, SQL, Python, and R skills.
- Research Google's culture: Review mission, values, and recent news.
- Prepare quant data examples: Use measurable outcomes from projects.
- Practice technical interviews: Focus on problem-solving and coding challenges.