Sr Scientist, Oncology Bioinformatics

Gilead Sciences•Foster City, CA

1d•Hybrid

About The Position

We are seeking a highly talented and motivated Senior Bioinformatics Scientist to take a lead role in statistical analysis of multi-omics and next generation sequencing data to support research projects from target evaluation to biomarker discovery with a focus in immune oncology and cancer biology. The successful candidate will have the chance to work in a fast-paced and highly collaborative environment and impact high-level decision-making on internal pipeline and external collaboration. The scientist will be responsible for developing and employing rigorous statistical modeling and cutting-edge bioinformatics methods to perform integrative large scale omics dataset analysis to enable research objectives. The successful candidate will be able to formulate scientific questions into coherent analytical efforts and communicate analysis results and scientific findings to project teams and across different research functions.

Requirements

Extensive hands-on experience in analyzing and interpreting RNA-Seq (bulk and single cell), WES, WGS, ATAC-Seq, CITE-Seq, and TCR-Seq data is required.
Strong statistics knowledge, such as probability theory, univariate and multi-variable analysis, unsupervised and supervised analysis, regression analysis, survival analysis, feature selection, and power analysis.
Excellent oral and written communication skills. Demonstrated capability to synthesize scientific questions into a coherent research effort and efficiently communicate scientific findings across different functional teams and present analysis results to project review teams and senior leader committees.
A proactive and self-motivated scientist with a strong work ethic and scientific rigor; ability to work in a dynamic environment and manage multiple projects in parallel and adapt to changing priorities.
Demonstrated track record of producing high-quality scientific results as an individual contributor and a team member.
Bachelor's Degree and Seven Years’ Experience OR Masters' Degree and Five Years’ Experience

Nice To Haves

The experience in analyzing other omics data (e.g., spatial transcriptome, Chip-Seq, MeRIP-seq, NanoString, multiplex qPCR, HT screening data sets) is a plus.
A PhD in bioinformatics, computational biology, biostatics, cancer genomics, or a related field with 3+ years of relevant work experience.
Industry experience is required.
Excellent interpersonal and communication skills that foster collaboration and teamwork.
Good understanding of cancer biology, immunology, molecular and cell biology.
Proficiency in R, Python, Perl, JAVA, or C/C++ programming languages.
Proficiency in high performance computing and cloud computing environments.
Outstanding track record of scientific and technical proficiency, evidenced by high quality publications in peer-reviewed journals.

Responsibilities

Develop and apply statistical and computational tools to analyze large scale omics and high dimensional data from internal, publicly available, commercial, and real-world datasets to enable novel target identification, target assessment, MoA elucidation, drug combination rationale, and patient stratification, etc.
Design and apply statistical techniques and machine learning algorithms to enable the discovery and evaluation of preclinical predictive and prognostic biomarkers for oncology projects.
Collaborate with cross-functional teams to analyze and interpret complex large datasets and efficiently communicate findings to non-computational scientists and senior leaders.