Senior Research Data Scientist, YouTube Resource Management
About The Position
In this role, you will be a part of YouTube Data Science, a team that directly influences and informs YouTube’s product and engineering leadership as it has a long history of working on projects that are at the heart of the business and have a seat at the table when it comes to the decisions that drive YouTube's continued success. Your mission is to improve decisions at YouTube with science. You will partner with stakeholders in solving problems in forecasting, simulations, constraint optimization and operations research. The US base salary range for this full-time position is $174,000-$252,000 + 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 [https://careers.google.com/benefits/].
Requirements
- 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 forecasting/time series.
Nice To Haves
- 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 working on constraint optimization, resource management, supply chain or operations research.
Responsibilities
- Engage with stakeholders across cross-functional projects and team settings to identify and clarify business or product questions to answer, while providing feedback to translate and refine business questions into tractable analysis, evaluation metrics, or mathematical models.
- Leverage custom data infrastructure or existing data models as appropriate, using specialized knowledge to design and evaluate models that mathematically express and solve defined problems with limited precedent.
- Execute scenario planning for live sport events such as NFL and the World Cup through complex simulations and modeling.
- Own the process of gathering, extracting, and compiling data across sources via relevant tools (e.g., SQL, R, Python), formatting, re-structuring, or validate data to ensure quality, and review the dataset to ensure it is ready for analysis.
- Forecast and allocate resource requirements covering TPU, Compute, Egress and other resources.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
