About the role
Denali Therapeutics is dedicated to defeating neurodegenerative diseases to deliver safe and effective medicines to patients and families. They are seeking a Data Scientist/Statistical Programmer to help shape their data and programming infrastructure, utilizing R in a regulated environment and contributing to the drug development process.
Responsibilities:
Support statistical programming deliverables including generation of data visualizations or summary reports to support internal decision making and regulatory interactions (IND/CTA filings, annual safety reporting, etc.); providing input for study protocols and clinical study reports; reviewing study randomization specifications, overseeing outsourced development of analysis data and results; and reviewing case report forms and external data transfer specifications.
Curate data for use with statistical reporting code and analytics applications.
Develop and manage reusable code for interactive data visualization and analytics tools for reporting and exploratory analysis.
Qualification:
At a minimum, a Bachelor's degree in Data Science, Mathematics, Statistics, Biostatistics, Bioinformatics, Biological Science, or related field.
Excellent communication skills and experience in representing teams.
Good R programming skills (including tidyverse, RMarkdown, Shiny, HTML widgets, and development of R packages), experience applying software development concepts, and proficiency in using Git/GitHub to create operational, robust, and well-documented code.
Strong data wrangling skills using R and database languages (e.g., SQL, NoSQL).
Able to create compelling data visualizations to help teams make correct data driven decisions, and able to effectively communicate results to team members.
Good understanding of statistical principles and methods.
Preferred:
At least one year of experience as a Statistical Programmer on a Biotech/Pharma Clinical Development Biometrics Team or with a similar team and experience supporting drug development, medical device development, or intervention studies.
Master's degree in Data Science, Mathematics, Statistics, Biostatistics, Bioinformatics, Biological Science, or related field.
Prior work experience with pharmacokinetic data and the neuroscience field, able to work in a Linux environment (including shell scripting), proficiency in languages or tools other than R (e.g., Python, Java, C++, SAS), containerization technologies such as Docker, Amazon Web Services, and experience with applying machine learning techniques.
Applied experience with CDISC/SDTM/ADaM data standards.
