Senior Statistician And Software Developer

Stata development duties include: researching the causal, statistical, and machine learning literature. For Machine Learning methods, work on decision trees, random forests, and gradient boosting machine algorithms. These algorithms are state-of-the-art methods that are used for data analysis and forecasting. Work on algorithms that use directed acyclic graphs (DAGs) to learn the underlying causal structure of data. Directed Acyclic Graphs (DAGs) are statistical objects that are used to represent the underlying structure of a dataset. Programming the above-mentioned methods into Stata using various programming languages, such as Mata and C++. Writing corresponding documentation and manual entries for Stata users. Ensure H2O software is integrated into Stata by writing wrapper functions, corresponding documentation, and manual entries. H2O is a machine learning software written in the Java language that is used to implement state-of-the-art machine learning algorithms. Review and provide feedback on code or documentation. Provide technical answers to Stata users regarding statistical techniques or software implementation. Provide answers to statistical questions posted on Statalist by users. Write blog posts regarding the implementation of different statistical techniques using Stata. Submit an article and accompanying Stata software that discusses and implements a new statistical method.
Education Required: PhD in Statistics
Experience Required: None
Special Requirements: Demonstrated knowledge of statistical/machine learning.