Principal Bioinformatics Scientist

Job Summary
Exelixis is seeking a highly motivated Principal Bioinformatics Scientist to join our team. As a key member of our Scientific Strategy group, you will be responsible for conducting computational analyses of clinical and multi-omics data sets to identify potential mechanisms of drug action and resistance and relationships between potential targets and cancer indications.

Key Responsibilities
Analyze genomic, transcriptomic, proteomic, and population data collected from real-world clinical data and correlate with clinical outcomes.
Provide expertise on tumor biology data sources, including single-cell RNA data sources, and tumor microenvironment (TME) mechanisms for Scientific Strategy Bioinformatics.
Perform independent data analyses and provide timely delivery of results with input on analysis goals from Scientific Strategy, Biotherapeutics, Discovery, Clinical Development, Commercialization Strategy and Planning, and other functions.
Collaborate across the organization with discovery, clinical development, and other staff to prioritize analysis plans.
Coordinate with Scientific Strategy colleagues, bioinformaticians, cloud computing engineers, and others as needed to collaboratively deploy code, analysis results, and data visualizations.
Provide imaginative vision for innovative data integration and analysis to elucidate tumor biology and/or tumor microenvironment biology.
Present analysis results with exceptional clarity.

Requirements
PhD in the Computational Biology discipline or related discipline and a minimum of 5 years of related experience; or,
Master's in Computational Biology or a related discipline and a minimum of 9 years of related experience; or,
Bachelor's in Computational Biology or a related discipline and a minimum of 11 years of related experience; or,
Equivalent combination of education and experience.
Experience with advanced data analysis tools and approaches in the pharmaceutical and biotech industries.
Demonstrated experience with clinical real-world data/evidence analysis.
Demonstrated ability to synthesize impactful bioinformatics data analysis plans for elucidating mechanisms in tumor and/or tumor microenvironment biology.
PhD preferred.
Demonstrated knowledge of aspects of tumor biology preferably including drug resistance mechanisms and/or tumor microenvironment drug targets and experience integrating knowledge into bioinformatics analysis plans.
Ability to read, understand, and summarize literature on tumor biology, as well as bioinformatics literature.
Demonstrated ability to work effectively across disciplines is required.
Skilled in different programming languages (minimally R and Python, Javascript a plus).
Skilled in employing large 'omics datasets as well as public genomic databases (e.g. TCGA, CPTAC, etc.).
Knowledgeable about using data sources, such as protein-protein interaction data (e.g. STRING, STITCH, BioGrid), cancer clinical data (e.g., TCGA, CPTAC), cellular data (e.g., DepMap, CMAP), and knowledgeable about valuating the limitations of the data (detailed knowledge of multiple proteomics data sources a plus).
Demonstrated understanding of working collaboratively to integrate data from multiple sources for comprehensive analyses (e.g., using GitHub, presenting data analysis plans, reviewing and summarizing technical publications).
Exceptional communication skills are required, with an emphasis on facilitating rapid progress in the computational analysis of biological data in a collaborative setting and on presenting analyses to non-data scientific staff at every level.
Significant experience with single-cell RNA sequencing data (scRNA-Seq) a plus.
Experience with machine learning and artificial intelligence methods a plus.

Working Conditions
Environment: in office at least 3 days a week.
Travel involves quarterly visits to Exelixis sites and attending 1-2 conferences per year.