Master's degree in a quantitative field (Statistics, Data Science, etc.)
5 years of analytics experience or 3 years with a PhD
Proficient in Machine Learning algorithms and statistical modeling
Skilled in statistical data analysis and experimental design (A/B testing)
Experience with causal inference techniques for treatment effects.
Responsibilities
Research and develop advanced analysis and causal inference methodologies for product opportunities.
Frame and solve ambiguous business problems, communicating data-driven solutions effectively.
Initiate and autonomously drive projects to completion, focusing on user advocacy and responsible growth.
Collaborate cross-functionally to influence product stakeholders and leadership.
Utilize AI tools to implement advanced statistical and machine learning solutions.
Benefits
Comprehensive health coverage
Retirement savings plan
Generous paid time off
Employee development programs
Flexible working locations (Mountain View, CA or New York, NY).
Full Job Description
info_outline X Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Mountain View, CA, USA; New York, NY, USA.
Minimum qualifications:
Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.
5 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 3 years of work experience with a PhD degree.
Experience with Machine Learning algorithms and statistical modeling.
Experience with statistical data analysis, experimental design (e.g., A/B testing), and causal inference.
Experience applying causal inference techniques to estimate treatment effects or perform counterfactual analysis.
Preferred qualifications:
8 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 6 years of work experience with a PhD degree.
Experience in scientific methodologies and Large Language Models
Experience performing product growth opportunity and headroom analysis.
Experience solving unstructured business problems and translating results into product recommendations.
Experience translating unstructured business problems into data-driven product recommendations
Ability to articulate scientific concepts to both technical and non-technical stakeholders.
About the job Google Search is the world's most trusted and knowledgeable health companion, activating seamless care-paths for every Health Journey. Health is one of Alphabet's top priorities, and this is a high-visibility role focused on evaluations, metrics, and user insights for AI answers in Search Health. You will have significant opportunities to influence product and engineering directions by creating and applying advanced statistical, Machine Learning (ML), and Large Language Model (LLM) methodologies to solve complex business problems.In Google Search, we're reimagining what it means to search for information - any way and anywhere. To do that, we need to solve complex engineering challenges and expand our infrastructure, while maintaining a universally accessible and useful experience that people around the world rely on. In joining the Search team, you'll have an opportunity to make an impact on billions of people globally.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
Research and develop advanced analysis, causal inference analysis of impact, and creative new methodologies (e.g., LLM-based methods) to identify product opportunities from various data sources and product headroom analysis for key AI features.
Frame and solve ambiguous business problems and communicate data-driven solutions effectively to stakeholders.
Initiate projects across the organization and drive them to completion autonomously while advocating for users and focusing on long-term responsible growth.
Interact cross-functionally as a thought partner to influence a wide range of product stakeholders and senior product leadership.
Leverage AI fluency and tools to drive advanced statistical and machine learning solutions for complex business challenges.
About Google
Google is a multinational technology company that specializes in Internet-related services and products. These include online advertising technologies, search engine, cloud computing, software, and hardware. Google was founded in 1998 by Larry Page and Sergey Brin while they were Ph.D. students at Stanford University. The company has grown tremendously since then and has become one of the most valuable companies in the world. Google's mission is to organize the world's information and make it universally accessible and useful.
