Senior Data Scientist, Product, Googler Technology and Engineering at Google

San Francisco, California, United States -

Full Time

Start Date

Immediate

Expiry Date

18 Dec, 25

Salary

229000.0

Posted On

19 Sep, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Science, Statistical Analysis, Python, R, SQL, Machine Learning, Analytics, Problem Solving, Data Manipulation, Visualization, KPI Development, Business Insights, Experimentation, AI, Advanced Analytics, Consulting

Industry

Software Development

Description

MINIMUM QUALIFICATIONS: * Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field. * 8 years of experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL) or 5 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. * 8 years of experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL). ABOUT THE JOB: We partner with teams across the company to apply Google's best data science techniques to Google's biggest enterprise opportunities. We collaborate with Research, Core Enterprise Machine Learning (ML), and ML Infrastructure teams to build solutions for our enterprise. The Google Technology Enterprise (GTE) Data Science team's mission is to transform Google Enterprise business operations, supply chain, Information Technology (IT) support, and internal tooling with Artificial Intelligence (AI) and Advanced Analytics. We enable operations and product teams to succeed in their advanced analytics projects through the use of differing engagement models, ranging from consulting to productionizing and deploying models. We also build cross-functional services for use across Corporate Engineering (Corp Eng) and educate product teams on advanced analytics and machine learning. The US base salary range for this full-time position is $156,000-$229,000 + 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 [https://careers.google.com/benefits/]. RESPONSIBILITIES: * Provide problem-solving thought leadership through proactive and strategic contributions; consistently use insights and analytics to drive decisions and alignment throughout the organization. * Work in a team covering problem definition, metrics development, data extraction and manipulation, visualization, creation, implementation of analytical/statistical models, and presenting to stakeholders. * Define and report Key Performance Indicators (KPIs) and launch impact as part of regular business reviews with the cross-functional and cross-organizational leadership team. Translate analysis results in business insights or product improvement opportunities. Work with Product Managers, User Experience, and Engineers to contribute to metric-backed annual and quarterly OKR settings. * Improve experimentation velocity and analysis turnaround time through adoption of self-service tools and improved processes. * Design and develop cutting-edge machine learning models to solve complex problems within the Enterprise Support space that solve actual business problems for Google.

Responsibilities

Provide problem-solving thought leadership and use insights and analytics to drive decisions across the organization. Collaborate with teams to define metrics, develop analytical models, and present findings to stakeholders.