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Position: Senior Data Scientist
Institution: Stanford University
Location: Stanford, California, United States
Duties: Work closely with the Faculty Director and the rest of the RegLab team to explore, identify, and implement research projects; Lead the design and development of multiple projects using state-of-the-art machine learning models, algorithms, statistical models, and other programs designed to improve the public sector; Work with large untapped data sets, such as: health and environmental enforcement data, mass adjudication records, high-resolution satellite imagery (15cm/pixel), and the largest publicly available corpus of legal text; Mentor and/or manage other data scientists and junior researchers
Requirements: A bachelor’s degree (MS or Ph.D. preferred) in a scientific or analytic field (e.g., data science, computer science, statistics, engineering, mathematics, economics, or a related field) and five years of (a) relevant professional experience or (b) combination of education and relevant professional experience; Knowledge of key data structures algorithms, and techniques pertinent to systems that support high volume, velocity, or variety datasets (including data mining, machine learning, NLP, data retrieval)
   
Text: Senior Data Scientist Work closely with the Faculty Director and the rest of the RegLab team to explore, identify, and implement research projects; Lead the design and development of multiple projects using state-of-the-art machine learning models, algorithms, statistical models, and other programs designed to improve the public sector; Work with large untapped data sets, such as: health and environmental enforcement data, mass adjudication records, high-resolution satellite imagery (15cm/pixel), and the largest publicly available corpus of legal text; Mentor and/or manage other data scientists and junior researchers A bachelor’s degree (MS or Ph.D. preferred) in a scientific or analytic field (e.g., data science, computer science, statistics, engineering, mathematics, economics, or a related field) and five years of (a) relevant professional experience or (b) combination of education and relevant professional experience; Knowledge of key data structures algorithms, and techniques pertinent to systems that support high volume, velocity, or variety datasets (including data mining, machine learning, NLP, data retrieval)
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