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Position: Data Scientist
Institution: Stanford University
Location: Stanford, California, United States
Duties: Act as the data and statistical leader across a variety of research projects; Prioritize and extract data from a variety of sources such as notes, survey results, medical data, and other big data sources, determine and maintain its accuracy and completeness; Determine additional data collection and reporting requirements; Design and customize analytical reports based upon data in the database. Oversee and monitor regulatory compliance for utilization of the data; Use system reports and analyses to identify potentially problematic data, make corrections, and eliminate root cause for data problems or justify solutions to be implemented by others
Requirements: Bachelor’s degree and three years of relevant experience or combination of education and relevant experience. An advanced degree (Master’s or PhD) is highly desired; Experience in a quantitative discipline such as economics, finance, statistics, political science, computer science, engineering, health economics, or biostatistics; Excellent writing and analytical skills; Mastery of R; Knowledge of causal inference methods
   
Text: Data Scientist Act as the data and statistical leader across a variety of research projects; Prioritize and extract data from a variety of sources such as notes, survey results, medical data, and other big data sources, determine and maintain its accuracy and completeness; Determine additional data collection and reporting requirements; Design and customize analytical reports based upon data in the database. Oversee and monitor regulatory compliance for utilization of the data; Use system reports and analyses to identify potentially problematic data, make corrections, and eliminate root cause for data problems or justify solutions to be implemented by others Bachelor’s degree and three years of relevant experience or combination of education and relevant experience. An advanced degree (Master’s or PhD) is highly desired; Experience in a quantitative discipline such as economics, finance, statistics, political science, computer science, engineering, health economics, or biostatistics; Excellent writing and analytical skills; Mastery of R; Knowledge of causal inference methods
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