Assistant, Statistical Research Programmer PT, Limited Term

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.