Job Description
In this position, the Data Scientist applies statistical methods and machine learning techniques to enhance AI tools for software developers. Developers benefit by addressing hurdles in productivity through data-driven insights from Tensor Processing Unit datasets. The role involves coding in Python, R, and SQL for analytics and experimentation design.
Google provides AI and infrastructure solutions at a massive scale for Google Cloud customers and billions of users worldwide. The company develops custom silicon like Tensor Processing Units to power AI models and global services. Google's AI team offers breakthrough capabilities in efficiency and reliability.
Daily activities include collaborating with engineering teams to collect high-quality data on developer processes. Professionals analyze issues to identify AI-driven solutions, define metrics for AI-powered tools, and forecast future needs using data trends. They work with modeling tools, present findings to leadership, and interact with machine learning teams for causal inference. The role demands knowledge of production workflows and dealing with multiple hypotheses in testing.
The US base salary range stands at $141,000-$202,000, plus bonus and equity. Full-time roles include benefits like healthcare and professional development opportunities. Positions allow for remote work flexibility depending on location.
Responsibilities
- Collaborate with engineering teams to instrument and gather high-quality data, laying the groundwork for understanding and enhancing AI products and developer productivity
- Perform deep analysis of developer processes and issues to pinpoint where AI-driven solutions can deliver the most significant impact
- Define and track the success of AI-powered developer tools
- Move beyond reactive data analysis to discover latent trends, forecast future requirements, and prove the return on investment of projects
- Present discoveries and insights to leadership, guiding data-centric decisions that will define the future of developer tools at Google
Requirements
- Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field
- 3 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a PhD degree
- PhD degree in Statistics, Math, Computer Science, Engineering, or related quantitative fields or Master's degree with 3 years of experience in quantitative areas
- 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 a PhD degree
- Experience in experiments (e.g., design of experiments, experiment logging, multiple hypothesis testing, causal inference)
- Experience working in a development lifecycle, defining requirements, checking in code, testing, staging, production
- Ability to be collaborative and to build excellent trust and relationships with cross-functional teams