Full-Time Clinical Data R Wrangler for clinical studies data on Type 1 Diabetes
Our focus in the Center for Applied Molecular Medicine (CAMM) is the discovery of biomarkers that are indicative of a person’s disease risk or status. The benefits of a technology to “personalize” medical treatment by accurately predicting disease and outcomes are hard to overestimate in terms of delivering accurate and effective care. The barriers to personalized medicine are both technological and biological. First, reliable approaches to routinely and rigorously measure the composition of biological samples must be developed, then approaches for interpreting those measurements to describe the state of a complex biological system are required. CAMM has engaged a highly inter-disciplinary team of clinicians, biologists, mathematicians, and physical scientists to approach these complex problems with new approaches and technologies.
CAMM is seeking an experienced clinical data wrangler to support data scientists and biostatisticians to analyze a wide range of data from clinical studies in Type 1 Diabetes.
1. Extracting, aggregating, annotating, and manipulating large clinical data sets
2. Creating fully documented R scripts to reproducibly perform data manipulations
3. Preparing and presenting project reports
4. Formally documenting processes
Demonstrable Personal Attributes:
• Ability to thrive in a fast-paced, multi-disciplinary environment
• Strong organizational skills
• Attention to detail
Knowledge and Skills:
• Ability to input, output, and manipulate data using the R statistical analysis platform. Sample code required.
• Facility with Microsoft Excel, Word, and PowerPoint.
• Working knowledge of relational databases, particularly Postgres.
• Experience with Linux shell scripting and command line tools a plus.
• Good writing and verbal communication abilities
• Experience with OMOP a plus
Education and Experience:
• Bachelor’s degree in computer science, engineering, information sciences or a related discipline. Master’s degree preferred.
• 2+ years’ experience in clinical data collection, transformation, management, and warehousing