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Job Details
Posted date: Jun 04, 2025
Location: Kirkland, WA
Level: Director
Estimated salary: $227,000
Range: $183,000 - $271,000
Description
Perform analysis utilizing relevant tools (e.g., SQL, R, Python). Provide problem-solving thought leadership through proactive contributions (e.g., suggests new analyses, infrastructure or experiments to drive improvements in the business).Own outcomes for projects by covering problem definition, metrics development, data extraction and manipulation, visualization, creation, and implementation of statistical models, and presentation to stakeholders.
Develop solutions, lead, and manage problems that may lack clear precedent by framing problems, generating hypotheses, and making recommendations from a product-specific experience.
Oversee the integration of cross-functional and cross-organizational project/process timelines, develop process improvements and recommendations, and help define operational goals and objectives.
Oversee the team's contributions and develop capabilities in the area of specialization.
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 Play Ads Data Science team works on a broad set of Ads analyses, and is involved in every part of the product lifecycle from brainstorming and ideation to shipping and monitoring. The team has a good mix of data science-led projects as well as experimentation and shaping of key product features.
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 $183,000-$271,000 + 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.
Qualifications
Minimum qualifications: Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.10 years of experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL) or 8 years of experience with a Master's degree.
Preferred qualifications: Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
12 years of experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL). 5 years of experience working on consumer ad-tech roles. Ability to manage product strategy and analytics, leveraging domain experience in Ads.
Extended Qualifications
Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.10 years of experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL) or 8 years of experience with a Master's degree.
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