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Single Cell Sequencing Jobs (NOW HIRING)

Pfizer

Senior Scientist, Cellular Genomics

Cambridge, MA · On-site

$94 - $156/hr

Hands-on experience of wet-lab genomic assay workflows, including sample processing, sequencing, single-cell, or spatial profiling methods sufficient to evaluate data quality and guide study design ...

Omics Empower

Technician

Darien, IL · On-site

Single-Cell Sequencing, Spatial Transcriptomics, or Metabolomics 🧬 Experience with NGS / molecular biology workflows 🎓 Bachelor's degree in Biology or a related life-sciences field -- Master ...

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How much do single cell sequencing jobs pay per hour?

As of Sep 9, 2026, the average hourly pay for single cell sequencing in the United States is $21.64, according to ZipRecruiter salary data. Most workers in this role earn between $16.83 and $27.16 per hour, depending on experience, location, and employer.

What is single cell sequencing?

Single cell sequencing is a cutting-edge technique used to analyze the genetic information of individual cells. Unlike traditional sequencing methods that average data from many cells, single cell sequencing allows researchers to study the unique gene expression, mutations, and cellular functions of each cell separately. This approach helps scientists understand cellular diversity, identify rare cell types, and uncover insights in fields like cancer research, immunology, and developmental biology.

What are the key skills and qualifications needed to thrive as a single cell sequencing scientist?

To excel as a Single Cell Sequencing Scientist, you need a solid background in molecular biology, genomics, and bioinformatics, typically supported by a relevant advanced degree. Proficiency with single cell sequencing platforms (such as 10x Genomics), next-generation sequencing (NGS) technologies, and data analysis tools like R or Python is essential. Strong analytical thinking, attention to detail, and effective communication skills help in interpreting complex data and collaborating across multidisciplinary teams. These competencies are crucial for generating high-quality results and driving innovative research in cellular biology.

What are some common challenges faced by professionals working in single cell sequencing, and how can they be addressed?

Professionals in single cell sequencing often encounter challenges such as sample preparation complexity, data analysis bottlenecks, and maintaining sample integrity to avoid contamination. Adapting to rapidly evolving technologies and protocols is also common, requiring continuous learning. Addressing these challenges involves staying updated with best practices, collaborating closely with bioinformaticians for data analysis, and participating in regular training or workshops to refine technical skills.

What is the difference between Single Cell Sequencing vs Single Cell Analyst?

AspectSingle Cell SequencingSingle Cell Analyst
Required CredentialsAdvanced degrees in biology, genomics, or related fields; experience with sequencing technologiesBachelor's or master's in biology, bioinformatics, or related fields; familiarity with sequencing data analysis
Work EnvironmentResearch labs, biotech companies, academic institutionsLaboratories, research facilities, biotech firms
Employer & Industry UsageUsed in genomics research, personalized medicine, cancer studiesRoles involve data analysis, sample preparation, and experiment support

Single Cell Sequencing refers to the technology and process of sequencing individual cells to study their genetic information, often requiring advanced technical skills. A Single Cell Analyst typically performs data analysis, sample preparation, and supports sequencing projects. While both roles work closely in genomics research, Single Cell Sequencing is more focused on the technical process, whereas Single Cell Analysts focus on data interpretation and laboratory support.

What other helpful pages are available for Single Cell Sequencing?

Other pages related to Single Cell Sequencing:

Infographic showing various Single Cell Sequencing job openings in the United States as of September 2026, with employment types broken down into 90% Full Time, and 10% Contract. Highlights an 90% In-person, and 10% Remote job distribution, with an average salary of $45,021 per year, or $21.6 per hour.

Computational Scientist II - Single Cell Genomics

South San Francisco, CA • On-site

Dawar Consulting
IT Services • 11 - 50 employees
Learn more about Dawar Consultingexternal

$80 - $100/hr

Other

Medical, Dental, Vision, Retirement

Re-posted 3 days ago

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

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