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.

• 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.

• 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, Nano String, 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.

• 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