info_outline XIn accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees. Benefits for this role include: Health, dental, vision, life, disability insurance Retirement Benefits: 401(k) with company match Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment Sick Time: 40 hours/year (increased to 69 hours/year for Seattle) including 5 discretionary sick days per instance Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks Baby Bonding Leave: 18 weeks Holidays: 13 paid days per year Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Mountain View, CA, USA; Kirkland, WA, USA; New York, NY, USA. Minimum qualifications: Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field. 8 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL) or 5 years of work experience with a Master's degree. Experience creating experiments and pilots to gather data and insights. Preferred qualifications: Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field. 8 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 Shopping is a comprehensive product search engine, a fast-growing product ads business, and an everyday essentials marketplace. We aim to revolutionize shopping by building great end-to-end user experiences that bring users, retailers, and manufacturers together. The Consumer Shopping Data Science team works on shopping products on various surfaces including Search, AI Mode, and Gemini. As a Data Scientist in Consumer Shopping organization, you will evaluate and improve Google's Shopping products. You will collaborate with a multidisciplinary team of Engineers and Product Managers on a wide range of problems. You will bring investigative excellence and statistical methods to the issues of measuring quality, improving consumer products, and understanding the behavior of our end-users, merchants, and partners. You will develop, organize and launch experiments and projects across Engineering and Product teams. Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $163000 - $237000 (USD) + 15% bonus target + equity + benefits Learn more about benefits at Google. Responsibilities Perform analysis utilizing relevant tools (e.g., SQL, R, Python). Help solve problems, narrowing down multiple options into the best approach, and take ownership of open-ended ambiguous business problems to reach an optimal solution. Build new processes, procedures, methods, tests, and components with foresight to anticipate and address future issues. Report on Key Performance Indicators (KPIs) to support business reviews with the cross-functional/organizational leadership team. Translate analysis results to business insights or product improvement opportunities. Build and prototype analysis and business cases iteratively to provide insights at scale. Develop comprehensive knowledge of Google data structures and metrics, advocating for changes where needed for product development. Research and develop analysis and methods to improve the quality of Google's user-facing products (e.g., application areas include AI Mode shopping product quality, and shopping search quality).