Data Science PhD Intern, 2027

Google's data scientists work within our Software Engineering organization, including Search, YouTube, and Google Ads. We analyze sets of data and continually run live experiments in order to help drive critical decisions at Google. Specifically, we support the development of innovative, highly scalable, next-generation technologies through research and advanced analysis. Google is and always will be an engineering company. We hire people with a broad set of technical skills who are ready to address some of technology's greatest challenges and make an impact on millions, if not billions, of users. At Google, engineers not only revolutionize search, they routinely work on massive scalability and storage solutions, large-scale applications and entirely new platforms for developers around the world. From Google Ads to Chrome, Android to YouTube, Social to Local, Google engineers are changing the world one technological achievement after another. Provide research on topics including Google's business model and search techniques. Produce quantitative and qualitative modeling of business dynamics, user behavior, and more. Identify areas for further investigation as well as creating innovative methods of analysis. Minimum qualifications: Currently enrolled in a PhD program in Statistics, Biostatistics, Computer Science, Mathematics, Operations Research, or a related technical field involving experimental design and quantitative analysis of experimental data, and in your penultimate year of study. Experience working with datasets using Python, R, SAS, MATLAB, or other statistical software. Experience with methods of statistical data analysis (e.g., linear models, hypothesis testing, multi-level models, Bayesian methods, etc.). Preferred qualifications: Experience with causal inference methods. Experience developing intellectual capital such as peer-reviewed publications. Ability to complete a minimum internship 13 weeks in the UK starting between May-July 2027. Currently enrolled in a PhD program in Statistics, Biostatistics, Computer Science, Mathematics, Operations Research, or a related technical field involving experimental design and quantitative analysis of experimental data, and in your penultimate year of study. Experience working with datasets using Python, R, SAS, MATLAB, or other statistical software. Experience with methods of statistical data analysis (e.g., linear models, hypothesis testing, multi-level models, Bayesian methods, etc.).