Data Science Intern at Denali - South San Francisco Clinical Data Science Intern Denali Therapeutics is dedicated to developing breakthrough therapies for neurodegenerative diseases through our deep commitment to degeneration biology and principles of translational medicine. We are searching for a highly motivated individual with strong statistical programming and problem solving skills to join us for a summer Clinical Data Science internship in the Biometrics group at Denali Therapeutics. A successful candidate will gain an in-depth understanding of drug development, experience working in a fast moving industry environment, and subject domain knowledge in the field of neurodegeneration. Responsibilities: - Opportunity to own a project with guidance from a mentor. The role may include collaboration with scientists, data analysis, model building, and presenting the results (e.g., investigating the advantages and disadvantages of using historical controls in a rare disease). - Data Wrangling and Curation: Develop an automated data curation process for consortium data that will involve data wrangling and built-in data integrity checks. - Create maintainable/reproducible code for 1) generating the curated data, 2) flexible visualization tool, 3) exploratory analysis (e.g., exploring neurodegenerative disease progression in ADNI or PPMI data). - Review relevant literature and study documentation to have an understanding of the endpoints of interest as it pertains to clinical drug development. Position requirements: - Currently enrolled or recent graduate in a MS, or PhD program in Biostatistics, Statistics, Computer Science, Mathematics, or related science discipline. - Proficiency with using R (tidyverse, RMarkdown) and GitHub to create operational, robust, well-documented code. - Strong interest in biotech/pharma. - Have excellent oral, written, and presentation skills. - Experience with creating interactive web apps (plotly dashboard, Shiny, htmlwidgets, javascript, D3), Docker, AWS (S3, Redshift), SQL, one or more programming languages other than R (e.g., Python, C++), and experience with disease related consortium data is preferred.