This role helps define the direction of computational biology efforts across Discovery and continues to adapt this strategy as needs evolve. This is a highly cross-functional role, collaborating with scientists to enable project advancement from early target validation through IND-enabling studies. This position develops tailored analytical approaches for a variety of data types and manages external partners as needed to achieve our goals. Through a combination of hands-on analysis and strategic oversight, this role has the opportunity to directly contribute to the advancement of Denali’s early-stage portfolio. Key Accountabilities / Core Job Responsibilities • Serves as the subject matter expert for the analysis of high-dimensional data, including bulk and single-cell/-nucleus transcriptomics data • Effectively collaborates with scientists across Discovery to design, analyze, and interpret in vitro and in vivo experiments to support projects across the portfolio • Performs rigorous, reproducible analysis across transcriptomic, genomic, and other high-dimensional datasets, adapting methods to fit the specific scientific question as needed • Develops and extends internal computational tools and workflows, as well as overseeing external analysis efforts as needed • Operates as a highly-independent contributor, defining analytical approaches, building solutions where none exist, and validating results with minimal oversight • Able to build and adapt analysis workflows using AI-assisted approaches while critically evaluating outputs for accuracy and scientific rigor • Applies best practices to code- and data-management, including workflow orchestration and version control; identifies opportunities for improvement where appropriate • Effectively communicates results to cross-functional teams and contributes to regulatory filings, patents, and publications Qualifications/Skills • PhD in a relevant field such as Computational Biology, Epidemiology, Neuroscience, Statistics, or similar with 3+ years relevant work experience in industry • Proven track record of analyzing single-cell/single-nucleus RNA-seq data, as evidenced by relevant publications, a deep understanding of relevant statistical methods, and experience using common software tools for analysis (e.g. Cell Ranger, CellBender, Seurat, scanpy, etc) • Additional experience with other high-dimensional data types (e.g., proteomics, mass spectrometry, human genetics) is a plus • Extensive experience in R or Python for analysis of high-dimensional biological data • Knowledge of version control (e.g., Git) and methods to generate analysis reports (e.g., R Markdown, Quarto). Experience building dashboards (e.g., with Shiny) is a plus • Track record of impactful research, including publications in peer-reviewed journals • Strong analytical and problem-solving skills, excellent oral and written communication skills Salary Range: $147,000.00 to $191,000.00 . Compensation for the role will depend on a number of factors, including a candidate’s qualifications, skills, competencies, and experience. Denali offers a competitive total rewards package, which includes a 401k, healthcare coverage, ESPP and a broad range of other benefits. Learn more at https://www.denalitherapeutics.com/careers This compensation and benefits information is based on Denali’s good faith estimate as of the date of publication and may be modified in the future.