Data Scientist, Product, Connected TV at Google
Google · San Bruno, United States Of America · Onsite
- Professional
- Office in San Bruno
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 (extracting insights, performing statistical analysis, or solving business problems), and coding (Python, R, SQL) (or 2 years of work experience with a Master's degree).
- 2 years of experience identifying and influencing opportunities for business/product improvement.
Preferred qualifications:
- Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
About the job
Help serve Google's worldwide user base of more than a billion people. Data Scientists provide quantitative support, market understanding and a strategic perspective to our partners throughout the organization. As a data-loving member of the team, you serve as an analytics expert for your partners, using numbers to help them make better decisions. You will weave stories with meaningful insight from data. You'll make critical recommendations for your fellow Googlers in Engineering and Product Management. You relish tallying up the numbers one minute and communicating your findings to a team leader the next.
YouTube Data Science is analyst team that influences and informs YouTube’s product and engineering leadership teams.
Connected TV (CTV) is a dynamic, fast-growing surface for YouTube. YouTube’s Connected TV Data Science team plays a pivotal role in fueling this growth by providing data-backed insights that directly drive the technical and business roadmaps.
In this role, you will partner with organizational leaders to guide strategic content acquisitions, sports and non-sports rights and more, in the name of driving efficiently driving growth for the business.
Responsibilities
- Perform analysis by utilizing relevant tools (e.g., SQL, R, Python). Using comprehensive technical knowledge, use custom data infrastructure or existing data models.
- Own the process of gathering, extracting, and compiling data across sources via relevant tools (e.g., SQL, R, Python). Format, re-structure, and validate data to ensure quality.
- Develop and standardize a comprehensive suite of growth metrics and health indicators to measure performance across YouTube product and feature areas.
- Provide investigative insights and recommendations to influence product feature development decisions, and with some guidance.
- Build and prototype analysis and business cases iteratively to provide insights at scale. Develop comprehensive knowledge of Google data structures and metrics.
