Biostatistician Intern

The EMMES Corporation•Rockville, MD

5h•Remote

About The Position

Biostatistician Intern US Remote Emmes Group: Building a better future for us all. Emmes Group is transforming the future of clinical research, bringing the promise of new medical discovery closer within reach for patients. Emmes Group was founded as Emmes more than 47 years ago, becoming one of the primary clinical research providers to the US government before expanding into public-private partnerships and commercial biopharma. Emmes has built industry leading capabilities in cell and gene therapy, vaccines and infectious diseases, ophthalmology, rare diseases, and neuroscience. We believe the work we do will have a direct impact on patients’ lives and act accordingly. We strive to build a collaborative culture at the intersection of being a performance and people driven company. We’re looking for talented professionals eager to help advance clinical research as we work to embed innovation into the fabric of our company. If you share our motivations and passion in research, come join us! Primary Purpose The Biostatistics Intern is responsible for working closely with biostatisticians on biomedical research projects across a variety of therapeutic areas. Interns meet with epidemiologists, project coordinators, and biomedical investigators and will contribute to the design, analysis and reporting of clinical research projects.

Requirements

Currently enrolled Masters/PhD student in statistics or biostatistics
Excellent analytical/problem solving skills
Strong attention to detail
Ability to manage priorities effectively
Familiarity with SAS or R programming

Responsibilities

Contribute to the review of sample size and other statistical aspects of study design
Perform statistical analysis and prepare summary reports and visualizations
Perform quality control (QC) for statistical deliverables prepared by other staff
Participate in presentations to biomedical investigators or manuscript preparation
Assist with review and finalization of research data sets for statistical analysis