Data Scientist
Job Description
Google's YouTube team seeks a Data Scientist in San Bruno, CA (hybrid) to translate business problems into analytical questions, build data driven models, and communicate quantitative solutions to leadership. The role carries a salary range of $164,450 to $211,000 per year and requires a PhD. This position offers the chance to influence products used by millions of users worldwide.
What you get
- Location: San Bruno, CA (hybrid)
- Compensation: $164,450 - $211,000 per year
- Education: PhD required
Responsibilities
- Collaborate with stakeholders to translate business needs into clear analytical questions, evaluation metrics, and mathematical models.
- Gather business goals, organizational context, and information regarding existing and upcoming data infrastructure to guide your analysis.
- Extract and compile large-scale data from multiple sources using SQL, R, and Python.
- Validate and prepare datasets for analysis by formatting, re-structuring, and ensuring data quality and integrity.
- Design and evaluate sophisticated models to mathematically solve complex problems with limited precedent. Apply scientific and statistical methods to evaluate and improve Google's products for millions of users worldwide.
Requirements
- Ph.D. in Computer Science, Statistics, Mathematics, Data Science, Economics, Physics, Operations Research, or a related field.
- Experience applying statistical or optimization methods to solve business problems.
- Ability to frame business problems posed by non-quantitative stakeholders into tractable quantitative problems.
- Presenting and defending quantitative solutions to senior leadership for implementation or to influence the business roadmap.
- Python or R for statistical analysis and algorithms.
- Ability to explain statistical concepts (Statistical Hypothesis Testing, Statistical Significance, Causal Inference, Confidence Intervals, Survival Analysis, Advanced Design of Experiments, ML/AI Evaluation) to non-quantitative audiences.
Technologies
- Python
- R
- SQL