Bioinformatics Scientist III

WaveCrest Staffing Group; Connecticut; Remote; USD 90,000 - 140,000; Full time

Job summary

WaveCrest Staffing Group is seeking a Bioinformatics Scientist III to support pharmaceutical research and biomarker discovery. The role focuses on NGS and multi-omics data analysis to identify targets for immunological diseases.

Responsibilities include developing pipelines, visualizing results with R Shiny and D3, and collaborating with cross-functional teams. 1-year contract, remote role based in Connecticut, USA.

Qualifications

• Master’s degree in Bioinformatics, Computational Biology, Genomics, Biostatistics, Computer Science, or a related STEM discipline with 1+ year of relevant experience; OR Bachelor’s degree in a STEM discipline with 7+ years of relevant experience.
• Experience in at least two areas: NGS analysis, functional genomics, large-scale statistical analysis, or multi-omics data integration.
• Strong programming skills in R and/or Python, with experience using relevant bioinformatics and Bioconductor packages.
• Hands‑on experience with UNIX/Linux, Bash scripting, and workflow management tools such as Nextflow.
• Knowledge of genomic databases, NGS data formats, and public bioinformatics resources.
• Experience with data visualization tools, preferably R Shiny and D3.
• Strong understanding of computational biology, genomics, and statistical methods for NGS analysis.
• Preferred Qualifications: Pharmaceutical or drug discovery research experience; Background in immunology or immunological diseases; Experience with single-cell sequencing and cloud computing.

Responsibilities

• Design, develop, and implement bioinformatics workflows for NGS data processing, analysis, visualization, and interpretation.
• Analyze genomic datasets, including bulk RNA-seq, scRNA-seq, and ATAC-seq.
• Perform statistical analysis, quality control, and multi-omics data integration to identify therapeutic targets and disease biomarkers.
• Mine internal and public genomic databases to characterize disease mechanisms and identify relevant biological pathways.
• Develop data visualization tools and automated reporting solutions using R Shiny, D3, and related technologies.
• Build, optimize, and maintain reproducible analytical pipelines using R, Python, UNIX/Linux, Bash, and Nextflow.
• Evaluate and benchmark computational tools and methods, applying innovative approaches when standard methods are insufficient.
• Interpret experimental results, recommend follow-up analyses, and communicate findings to cross-functional research teams.
• Stay current with scientific literature and emerging bioinformatics methodologies.
• Maintain accurate documentation, data integrity, and compliance with SOPs and applicable regulations.

Skills

NGS analysis

multi-omics integration

statistical analysis

data visualization

Education

Master's degree in Bioinformatics/Computational Biology/Genomics

Bachelor's degree in STEM with 7+ years experience

Tools

R

Python

Nextflow

UNIX/Linux

Bash scripting

R Shiny

D3

Job description

Our client is a global, research-driven pharmaceutical manufacturer focusing on treatment options for diseases and conditions for which there is no satisfactory treatment option to date. The company is looking for a Bioinformatics Scientist III to join the team. This is an amazing opportunity to work on cutting edge treatments and make a difference!

Job Summary

We are seeking a Bioinformatics Scientist to support pharmaceutical research, therapeutic target identification, and biomarker discovery, with a focus on immunological diseases. The candidate will develop and implement NGS and multi-omics data analysis workflows, analyze complex genomic datasets, and translate computational findings into actionable biological insights to support drug discovery and research initiatives.

Location: Role based in Conneticut (Remote role)

Job type: 1-year contract

Key Responsibilities

• Design, develop, and implement bioinformatics workflows for NGS data processing, analysis, visualization, and interpretation.
• Analyze genomic datasets, including bulk RNA-seq, scRNA-seq, and ATAC-seq.
• Perform statistical analysis, quality control, and multi-omics data integration to identify therapeutic targets and disease biomarkers.
• Mine internal and public genomic databases to characterize disease mechanisms and identify relevant biological pathways.
• Develop data visualization tools and automated reporting solutions using R Shiny, D3, and related technologies.
• Build, optimize, and maintain reproducible analytical pipelines using R, Python, UNIX/Linux, Bash, and Nextflow.
• Evaluate and benchmark computational tools and methods, applying innovative approaches when standard methods are insufficient.
• Interpret experimental results, recommend follow-up analyses, and communicate findings to cross-functional research teams.
• Stay current with scientific literature and emerging bioinformatics methodologies.
• Maintain accurate documentation, data integrity, and compliance with SOPs and applicable regulations.

Qualifications

• Master’s degree in Bioinformatics, Computational Biology, Genomics, Biostatistics, Computer Science, or a related STEM discipline with 1+ year of relevant experience; OR
• Bachelor’s degree in a STEM discipline with 7+ years of relevant experience.
• Experience in at least two areas: NGS analysis, functional genomics, large-scale statistical analysis, or multi-omics data integration.
• Strong programming skills in R and/or Python, with experience using relevant bioinformatics and Bioconductor packages.
• Hands‑on experience with UNIX/Linux, Bash scripting, and workflow management tools such as Nextflow.
• Knowledge of genomic databases, NGS data formats, and public bioinformatics resources.
• Experience with data visualization tools, preferably R Shiny and D3.
• Strong understanding of computational biology, genomics, and statistical methods for NGS analysis.
• Preferred QualificationsPharmaceutical or drug discovery research experience.
• Background in immunology or immunological diseases.
• Experience with single-cell sequencing and multi-omics data integration.
• Familiarity with cloud computing and automated analytical workflows.