Senior Research Scientist, Computational Biology

Category:

Life Science

Employment Type:

Contract

Reference:

BH-385334

Yoh is hiring a highly motivated and skilled Senior
Research Scientist,
Computational Biology
for our South San Francisco, CA client. This role offers a unique opportunity to contribute to both early- and late-stage drug discovery programs through advanced computational analyses.

Industry: Discovery and Research
Location: South San Francisco, CA
Compensation: $65-85/hr (based upon experience)
Type: Contract / On-site (full-time)

Job Functions:

• Lead and support computational investigations across the drug discovery pipeline, including: Biomarker discovery for late-stage programs; and Target identification and mechanism of action studies for early-stage programs.
• Analyze and interpret multi-omics and CRISPR screening datasets from internal and public sources to elucidate drug mechanisms.
• Collaborate closely with cross-functional teams to test hypotheses and accelerate research through data-driven insights.
• Present findings clearly and effectively to project teams and broader scientific audiences.
• Develop a strong understanding of the cancer biology relevant to therapeutic programs to enhance analytical impact.

• Proficiency in analyzing diverse omics data types (e.g., transcriptomics, proteomics, metabolomics) from in vitro, in vivo, and clinical sources.
• Experience with:
• Whole genome/exome sequencing (WGS/WES), including mutation calling and variant annotation.
• Functional genomics datasets, particularly CRISPR screens.
• Oncology-focused datasets and resources such as TCGA, DepMap, and others.
• Non-NGS omics platforms (e.g., Mass Spec, Olink, Nanostring).

• Familiarity with machine learning techniques for multi-omics integration and predictive modeling.
• Knowledge of non-linear modeling, optimization, Bayesian methods, and causal inference approaches.
• Strong technical skills in R, Python, & JavaScript, with a strong foundation in biology and hands-on laboratory experience.
• Comfort working with local or commercial large language models (LLMs) and integrating them into analytical workflows.
• Strong coding practices, including version control and software engineering principles.