Minimum qualifications:- 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.
- Experience with deep learning, machine learning, machine learning architecture, data analysis, distributed computing.
Preferred qualifications:- 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.
Responsibilities- Collaborate with teams to define relevant questions about advertising effectiveness, incrementality assessment, the impact of privacy, user behavior, brand building, targeting, bidding etc, then develop and implement quantitative methods to answer them.
- Apply causal inference methods to design experiments, establish causality, assess attribution and answer strategic questions using data.
- Analyze large, complex data sets by solving difficult, non-routine problems, using advanced analytical methods, conducting end-to-end analyses that include data gathering and requirements specification, exploratory data analysis (EDA), model development, and written and oral delivery of results to business partners and executives.
- Partner cross-functionally to deliver business recommendations (e.g., cost-benefit analysis, experimental design, use of privacy preserving methods such as differential privacy), presenting findings effectively to stakeholders at multiple levels to drive decisions.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $147000 - $210000 (USD) 15% bonus target equity benefits
Learn more about benefits at Google .
