Summary

The Epidemiology Program is the largest program devoted to pediatric cancer epidemiology in the US. The Program currently has several funded research projects focused on pediatric cancer etiology and survivorship. Epidemiology Program faculty also conduct and support research broadly related to pediatrics (e.g., studies of congenital anomalies, infectious diseases, and nutrition). 

Daily activities include data cleaning, analysis, and visualization in R, Python, and similar statistical software environments; preparing publication-quality tables and figures to summarize datasets and statistical models; technical writing (e.g., comprehensive and concise written summaries of methods and results); documenting and maintaining code and datasets in accordance with the Program's Standard Operating Procedures; identifying and implementing statistical methods described in the peer-reviewed literature, on pre-print servers, and in other sources as appropriate to support Program faculty's broad research portfolio; and assisting with data management.

Job Duties

• Works with Program faculty to identify and rigorously implement cutting-edge statistical techniques to analyze epidemiological and molecular data for studies of cancer and other pediatric conditions.
• Prepares publication-quality tables, figures, and technical summaries for publication in conference proceedings, peer-reviewed manuscripts, preprint servers, and other scientific forums in R, Python, PowerPoint, and Word.
• Adheres to Program Standard Operating Procedures (SOPs) for data storage and documentation of work.
• May prepare research presentations and draft peer-reviewed manuscripts.
• Assists other members of the epidemiology program in adapting statistical software for their needs.
• Complies with all applicable institutional, state, and federal data security requirements.
• Performs other job-related duties as assigned.

Minimum Qualifications

• Bachelor's degree in Statistics, Biostatistics or a related field.    
• Two years of relevant experience.

Preferred Qualifications

• Master's degree in a related field.
• Experience with command line statistical programming and data visualization in R.