Principal Scientist, Oncology Bioinformatics

Role Summary

We are seeking a highly talented and motivated Principal 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 work in a fast-paced and highly collaborative environment, influencing high-level decision-making on internal pipeline and external collaboration. The role involves developing and applying rigorous statistical modeling and cutting-edge bioinformatics methods to perform integrative large-scale omics dataset analysis to enable research objectives, and communicating results to project teams and across research functions. This role will sit in Foster City, CA.

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.
• 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.

Qualifications

• Required: Bachelor's Degree and Eight Years’ Experience
• Required: Master’s Degree And Six Years’ Experience
• Required: Ph.D.
• Preferred: Extensive hands-on experience in analyzing and interpreting RNA-Seq (bulk and single cell), WES, WGS, ATAC-Seq, CITE-Seq, and TCR-Seq data. Experience with other omics data (spatial transcriptome, ChIP-Seq, MeRIP-seq, NanoString, multiplex qPCR, high-throughput screening data) is a plus.
• Preferred: Strong statistics knowledge (probability theory, univariate and multivariate analysis, unsupervised and supervised learning, regression, survival analysis, feature selection, power analysis) and excellent oral/written communication. Ability to synthesize scientific questions into coherent research and communicate findings across teams and to leadership. Proactive, self-motivated, able to manage multiple projects, and capable of delivering high-quality results as an individual contributor and team member.
• Preferred: PhD in bioinformatics, computational biology, biostatistics, cancer genomics, or related field with 8+ years of relevant pharmaceutical/biotech industry experience.
• Preferred: Excellent interpersonal and communication skills; strong understanding of cancer biology, immunology, molecular and cell biology.
• Preferred: Proficiency in R, Python, Perl, JAVA, or C/C++ programming languages.
• Preferred: Proficiency in high performance computing and cloud computing environments; strong publication record in peer-reviewed journals.

Skills

• Bioinformatics and statistical analysis of multi-omics data
• Machine learning and statistical modeling
• Data integration across internal, external, and real-world datasets
• Communication of complex analytical results to cross-functional teams and leadership
• Programming: R, Python, Perl, Java, or C/C++
• Experience with HPC and cloud computing environments