Assistant, Statistical Research Programmer PT, Limited Term

Posting Details Position Information Position Title Assistant, Statistical Research Programmer PT, Limited Term Position Type Limited-Term Job Number SA74224 Full or Part Time part-time 0-19 hours weekly Fair Labor Standard Act Classification Non-Exempt Anticipated Pay Range $30.00 Pay Range Information Chapman University is required to provide a reasonable estimate of the compensation range for this position. This range takes into account a variety of factors that are considered in making compensation decisions, including experience, skills, knowledge, abilities, education, licensure and certifications, and other business and organizational needs. Salary offers are determined based on the final candidate's qualifications and experience, as well as internal equity and other internal factors. The anticipated pay range is not a promise of a particular wage. Position Summary Information Job Description Summary The role of the Assistant Statistical Research Programmer is integral in a dynamic multidisciplinary setting, supporting research initiatives encompassing a diverse array of critical subjects, including healthcare and health policy. This position will work closely with the PI and collaborators in creating, managing, and analyzing large and complex data sets. This position is part-time up of up to19 hours a week. Responsibilities Work closely with the PI and collaborators in creating, managing, and analyzing large data sets, for example, using Python on IQVIA databases that contain billions of claims records and dispensing records. Assist faculty and graduate researchers with statistical modeling, including regression, survival analysis, cost-effectiveness modeling, and multilevel modeling. Contribute to continuous improvement of departmental data infrastructure and workflow efficiency. Support research projects involving large administrative claims, EHR, survey, or clinical trial data. Collaborate with external collaborators in implementing machine learning algorithms. Perform other duties as assigned. Required Qualifications Bachelor's degree in Statistics, Biostatistics, Data Science, Computer Science, or a related field.

Python, SAS, or R for data management and statistical analysis. Exceptional problem-solving abilities with a solid understanding of statistical methods Good, Strong interpersonal and communication skills Ability to produce careful and detail-oriented work Ability to work in a team environment. A minimum of one year of experience in statistical programming with Python, SAS, or R, with a preference for candidates proficient in at least two of the mentioned languages. Desired Qualifications Master's Degree in related field. A good understanding of statistical methods for geospatial epidemiology (e.g., ArcGIS and preferably SaTScan™). Experience in writing and preparing manuscripts for publication. Thorough understanding and knowledge of epidemiological study design. Previous clinical or research training. Special Instructions to Applicants Chapman University is an equal opportunity employer that provides equal employment opportunities to all individuals, regardless of their protected characteristics. All qualified applicants and employees are encouraged to apply and will receive consideration for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity, gender expression, national origin, ancestry, citizenship status, physical disability, mental disability, medical condition, military and veteran status, marital status, pregnancy, genetic information or any other characteristic protected by state or federal law. Applicants for Staff and Administrator positions must be currently authorized to work in the United States on a full-time basis. The offer of employment is contingent upon satisfactory completion and outcomes of a criminal background screening and returning to the Office of Human Resources a signed original acceptance of the Chapman University Agreement to Arbitrate. Minimum Number of References Maximum Number of References