Computational Scientist II - Single Cell Genomics

Dawar Consulting; South San Francisco (CA); On-site; USD 73,873 - 105,214; Full time

Benefits offered by this job

Medical benefits

Dental benefits

Vision benefits

Paid sick leave

401K

Job summary

Dawar Consulting is seeking a Computational Scientist II for a long-term contract in South San Francisco, CA. The role focuses on single-cell genomics and therapeutic discovery, analyzing large datasets and building computational pipelines using Python. Qualifications include a Ph.D.

in a quantitative life science field, strong scRNA-seq experience, and expertise in Python and statistics. Collaboration across multidisciplinary teams is essential for delivering biological insights that advance

Qualifications

• Ph.D. in a quantitative life science or related field.
• Experience analyzing large-scale single-cell RNA sequencing (scRNA-seq) datasets.
• Strong Python programming for scientific computing and data analysis.
• Excellent analytical and collaborative skills.

Responsibilities

• Analyze and interpret large-scale single-cell sequencing datasets.
• Develop and optimize workflows for Perturb-seq, CROP-seq, Sci-Plex and other functional genomics studies.
• Apply statistical and computational methods to identify biological mechanisms, therapeutic targets, and treatment responses.
• Collaborate with biologists, chemists, computational scientists, and cross-functional research teams to translate complex data into actionable insights.
• Develop reproducible data analysis pipelines using Python.
• Perform quality control, data integration, visualization and statistical analysis of large-scale genomics datasets.
• Integrate multimodal datasets, including single-cell, genomic, and clinical data, to support research and therapeutic development.
• Present findings through scientific reports, presentations, and collaborations with internal research teams.
• Maintain well-documented, reproducible computational workflows and contribute to continuous process improvements.

Skills

Python

Statistics

scRNA-seq

Data analysis

NGS

Communication

Education

Ph.D. in Computational Biology / Bioinformatics / CS / Statistics / Mathematics

Tools

Nextflow

Snakemake

SLURM

Job description

Computational Scientist II - Single Cell Genomics

South San Francisco, United States | Posted on 07/08/2026

Our Client, a world leader in Biotechnology is looking for a Computational Scientist II for SSF, CA

Job Duration: Long Term Contract (Possibility Of Extension)

Pay Rate: $65/hr on W2

Company Benefits: Medical, Dental, Vision, Paid Sick leave, 401K

This role is focused on advancing therapeutic discovery through high-content perturbation screening and single-cell genomics. This role will involve analyzing large-scale sequencing datasets, developing computational pipelines, and collaborating with multidisciplinary teams to generate biological insights that support drug discovery.

Key Responsibilities

• Analyze and interpret large-scale single-cell sequencing datasets (scRNA-seq) generated from high-content perturbation experiments.
• Develop and optimize computational workflows for Perturb-seq, CROP-seq, Sci-Plex, and other sequencing-based functional genomics studies.
• Apply statistical and computational methods to identify biological mechanisms, therapeutic targets, and treatment responses.
• Collaborate with biologists, chemists, computational scientists, and cross-functional research teams to translate complex data into actionable insights.
• Develop reproducible data analysis pipelines using Python and bioinformatics tools.
• Perform quality control, data integration, visualization, and statistical analysis of large-scale genomics datasets.
• Integrate multimodal datasets, including single-cell, genomic, and clinical data, to support research and therapeutic development.
• Present findings through scientific reports, presentations, and collaborations with internal research teams.
• Maintain well-documented, reproducible computational workflows and contribute to continuous process improvements.

Required Qualifications

• Ph.D. in Computational Biology, Bioinformatics, Computer Science, Statistics, Mathematics, or a related quantitative life science discipline.
• Proven experience analyzing large-scale single-cell RNA sequencing (scRNA-seq) datasets.
• Strong programming skills in Python for scientific computing and data analysis.
• Solid background in statistics, probabilistic modeling, and computational data analysis.
• Experience working with next-generation sequencing (NGS) and genomics datasets.
• Excellent analytical, communication, and problem-solving skills.
• Demonstrated ability to collaborate effectively in multidisciplinary research environments.
• Strong publication record demonstrating scientific contributions.

Preferred Qualifications

• Experience with Perturb-seq, CROP-seq, Sci-Plex, or other CRISPR-based perturbation screening technologies.
• Experience with CRISPR functional genomics and single-cell perturbation analysis.
• Knowledge of multimodal data integration, including genomic, transcriptomic, and clinical datasets.
• Experience using workflow management systems such as Nextflow or Snakemake.
• Experience working on High Performance Computing (HPC) environments using SLURM.
• Familiarity with cloud computing, reproducible workflows, and collaborative software development practices.

If interested, please send us your updated resume at

Single Cell Sequencing, Pertub-Seq, Slurm, HPC, Computational Biology