Data Scientist III, Product, YouTube Shorts

Minimum qualifications:

• Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, a related quantitative field, or equivalent practical experience.
• 3 years of experience with analysis applications (i.e., extracting insights, performing statistical analysis, or solving business problems), and coding (e.g., Python, R, SQL).

Preferred qualifications:

• 5 years of work experience with analysis applications (i.e., extracting insights, performing statistical analysis, or solving business problems), and coding (Python, R, SQL).

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 US base salary range for this full-time position is $122,000-$178,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. 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

• 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 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.