Business Data Scientist, Statistics, Platform Analytics

Business Data Scientist, Statistics, Platform Analytics at Google

Applicants in San Francisco: Qualified applications with arrest or conviction records will be considered for employment in accordance with the San Francisco Fair Chance Ordinance for Employers and the California Fair Chance Act.

Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Sunnyvale, CA, USA; San Francisco, CA, USA.

About the job

In this role, you will be using data to solve problems and you will be a key partner to stakeholders across product, operations, and engineering, helping to drive our strategy by analyzing the entire customer journey. You will address a wide range of issues, from optimizing product features and user behavior to analyzing the customer support experience and streamlining internal processes. You will use your investigative and statistical skills to make data-informed decisions across the board.

The US base salary range for this full-time position is $141,000-$202,000 + 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.

Minimum qualifications:

• Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience.
• 3 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a relevant PhD degree.
• Experience analyzing data from various sources such as product instrumentation, customer support systems, and internal operational tools.
• Experience with SQL, Python or R programming including advanced data analysis, statistical modeling, and data visualization.

Preferred qualifications:

• PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
• 4 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a relevant PhD degree.
• Experience in Customer Support or Support-adjacent role.
• Experience with Large Language Models (LLMs), including their application in solving business problems.
• Experience in intelligent autonomous agents, including their design, development, evaluation, and deployment.
• Experience with cloud platforms (e.g., Google Cloud Platform) and their AI/ML services, particularly those related to LLMs and generative AI.

Responsibilities

• Partner with product, operations, and engineering stakeholders to prioritize opportunities for improvement; collaborate with partner teams to define data requirements and build foundational datasets for key business and product initiatives.
• Drive and separately scope and analysis projects from inception to completion, defining success metrics and managing stakeholder communication along the way; design, execute, and analyze split-testing (A/B) experiments on product features, internal tools, and operational workflows to measure their impact.
• Apply causal inference and advanced statistical modeling to measure the impact of critical product and business initiatives and understand their key drivers.
• Manage analyses of the user journey to identify friction points and opportunities; translate investigative findings into actionable insights and narratives for various stakeholders.
• Perform opportunity sizing for new product and business initiatives to inform the roadmap and resource allocation.

Key skills/competency

• Data Analysis
• Statistical Modeling
• Python
• R
• SQL
• Causal Inference
• A/B Testing
• Machine Learning
• Google Cloud Platform
• Problem Solving