About the job

Are you interested in launching impactful features on Search to deliver answers to users across the globe, while also redefining how the world discovers information by leveraging AI to build 0→1 products? Our mission is to bring new users to vertical experiences and help existing users get the most out of the existing verticals. Our mandate is to accelerate products that have product market fit, identify common patterns and opportunities, and scale impact to all verticals as quickly as possible. A fast-moving team who is obsessed with learning and landing real impact quickly.

As a Search Verticals Data Scientist, you will develop advanced statistical and other analytical methods to identify growth opportunities, such as emerging user needs, user and lifecycle segmentation, conversion, churn and win-back prediction, targeting, uplift modeling, value estimation. You will autonomously drive projects from start to finish, solve complex business problems, and communicate solutions effectively. By interacting cross-functionally and influencing executive leadership, you will advocate for users and focus on sustainable, long-term growth. This role involves understanding a wide range of search products, from GenAI to simple UI optimization, and using logs, surveys, and human-eval driven methods to design and validate solutions.

The US base salary range for this full-time position is $138,000-$198,000 + 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.

Responsibilities

• Research and develop advanced analysis, forecasting, experimentation, ML and optimization methods to identify growth opportunities (e.g., forecasting at scale, user segmentation, user cohort or causal inference modeling, and churn prediction).

• Initiate projects inside and across the organization and drive to completion autonomously.

• Frame and solve ambiguous business problems and communicate the solutions effectively.

• Interact cross-functionally, be a thought partner and influence a wide range of product stakeholders.

• Communicate clearly and persuasively and to influence executive product leadership.

Minimum qualifications

• Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.

• 5 years of work experience with analysis applications (e.g., extracting insights, performing statistical analysis, or solving business problems), and coding (e.g., Python, R, SQL), or 2 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.

• Experience working with consumer-facing products.

• Experience working with 0 to 1 products.