Senior Staff Data Scientist, Product

5 Months ago • 10-15 Years • $227,000 PA - $320,000 PA

Data Analysis

Job Description

This Senior Staff Data Scientist role supports Google's billion-plus users by providing quantitative insights and strategic perspectives to partners. Responsibilities include performing analysis using SQL, R, and Python; leading projects combining analytical and organizational complexity; owning projects end-to-end; addressing ambiguous problems; overseeing cross-functional project timelines; and providing direction to team members. The ideal candidate will weave data-driven stories, make impactful recommendations, and effectively communicate findings to stakeholders. The role involves defining operational goals and objectives. The position requires strong analytical and communication skills and experience in statistical modeling and data manipulation.

Good To Have:

Master's degree in quantitative field
15+ years experience in analytics

Must Have:

Bachelor's degree in quantitative field
10+ years experience in analytics
Proficiency in SQL, R, Python
Strong analytical & communication skills
Statistical modeling & data manipulation expertise
Project leadership & management skills

Perks:

Bonus
Equity
Benefits

Add these skills to join the top 1% applicants for this job

cross-functional

unity

data-science

python

sql

Minimum qualifications:

Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
13 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL) (or 10 years work experience plus a Master's degree).

Preferred qualifications:

Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
15 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., 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.

Google is an engineering company at heart. We hire people with a broad set of technical skills who are ready to take on some of technology's greatest challenges and make an impact on users around the world. At Google, engineers not only revolutionize search, they routinely work on scalability and storage solutions, large-scale applications and entirely new platforms for developers around the world. From Google Ads to Chrome, Android to YouTube, social to local, Google engineers are changing the world one technological achievement after another.

The US base salary range for this full-time position is $227,000-$320,000 + 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 utilizing relevant tools (e.g., SQL, R, Python). Direct projects that combine analytical and organizational complexity towards clear, sound, and actionable decisions.
Own projects end-to-end, covering problem definition, metrics development, data extraction and manipulation, visualization, creation, and implementation of analytical/statistical models, and presentation to stakeholders.
Address ambiguous or new problems by using the capabilities of existing systems and collaborate to turn broad problems into work for the team.
Oversee the integration of cross-functional and cross-organizational project/process timelines, drive improvements and recommendations, and define operational goals and objectives.
Provide direction and accomplish results through leading/impacting the contributions of others.