Remote Scientist III – Computational Biology / Bioinformatics

Remote Scientist III – Computational Biology / Bioinformatics

Position Details:

• Job Title: Scientist III – Computational Biology / Bioinformatics
• Requisition Number: 37793921
• Work Arrangement: Remote
• Work Schedule: 40 hours per week
• Contract Duration: 12-Month Contract

Sigma Systems is currently seeking a Remote Scientist III – Computational Biology/Bioinformatics to support inflammation and immunological disease research. This contract opportunity is ideal for a skilled computational scientist with expertise in bioinformatics, next-generation sequencing (NGS), multi-omics data analysis, genomics, and computational approaches to identify novel therapeutic targets and disease biomarkers.

Job Summary:

The Scientist III will contribute to inflammation and immunological disease research by designing, implementing, and deploying bioinformatics workflows for processing, analyzing, integrating, visualizing, and interpreting complex biological datasets. The successful candidate will apply computational biology, statistical analysis, and data mining techniques to support therapeutic target identification and disease biomarker discovery.

The role requires strong programming skills, hands-on experience with NGS data analysis, and the ability to collaborate with computational biologists and multidisciplinary scientific teams to develop innovative analytical methods and generate actionable scientific insights.

Key Responsibilities:

• Design, implement, and deploy NGS data analysis workflows to support therapeutic target identification and disease biomarker discovery.
• Analyze and interpret genomic datasets, including bulk RNA-seq, single-cell RNA-seq (scRNA-seq), and ATAC-seq.
• Develop and apply bioinformatics methods for functional genomics, statistical analysis, and multi-omics data integration.
• Process, integrate, visualize, and mine complex datasets from internal, collaborative, and public databases.
• Identify potential drug discovery targets, disease biomarkers, and downstream biological effects relevant to immunological diseases.
• Select, evaluate, and benchmark computational methods and tools for bioinformatics analysis.
• Define and perform appropriate quality control (QC) measures to ensure the accuracy, reliability, and integrity of analytical results.
• Develop innovative analytical approaches when standard methods are insufficient to address scientific challenges.
• Automate data processing, analysis workflows, and results reporting and delivery.
• Develop and maintain well-designed, documented, and reproducible code.
• Use data visualization tools and techniques, including R Shiny and D3, to communicate complex analytical findings.
• Collaborate with computational biologists and multidisciplinary research teams to solve scientific problems.
• Interpret experimental results, recommend appropriate follow-up analyses, and propose new avenues of investigation.
• Review relevant scientific literature to stay current with emerging computational methods, tools, and best practices.
• Present analytical results and scientific interpretations to colleagues, collaborators, and stakeholders.
• Contribute to the preparation of protocols, standard operating procedures (SOPs), technical reports, and scientific documentation.
• Maintain accurate records and uphold data integrity, ethical standards, and applicable regulatory requirements.

Required Qualifications:

• Master's degree from an accredited institution in a relevant scientific discipline, such as:
  • Bioinformatics
  • Computational Biology
  • Computer Science
  • Genomics
  • Biostatistics
  • A related scientific or STEM discipline
• At least 1 year of relevant experience with a master's degree, or a bachelor's degree in a STEM discipline with at least 7 years of relevant experience.
• Strong scientific understanding and hands-on experience in bioinformatics.
• Experience analyzing next-generation sequencing (NGS), functional genomics, large-scale genomic datasets, or multi-omics data.
• Experience analyzing one or more of the following:
  • Bulk RNA sequencing (RNA-seq)
  • Single-cell RNA sequencing (scRNA-seq)
  • ATAC sequencing (ATAC-seq)
• Strong programming skills in Python and/or R.
• Experience working with Unix/Linux environments and Bash shell scripting.
• Knowledge of computational methods for NGS analysis and familiarity with public bioinformatics databases and genomic data formats.
• Experience with statistical analysis, data processing, visualization, and interpretation of complex biological datasets.
• Familiarity with relevant R/Bioconductor packages and computational biology tools.
• Ability to develop well-structured, documented, and reproducible code.
• Strong analytical, troubleshooting, and problem-solving skills.
• Excellent written and verbal communication skills.
• Ability to work independently and collaboratively in a multidisciplinary scientific environment.

Preferred Qualifications:

• Experience in pharmaceutical research, drug discovery, or immunological disease research.
• Background in immunology, inflammation, immune responses, or related biological research.
• Experience with multi-omics data integration and interpretation.
• Familiarity with workflow orchestration and pipeline development tools, including Nextflow.
• Experience with data visualization technologies, including R Shiny and D3.
• Experience with cloud computing environments and large-scale data analysis.
• Knowledge of public genomic and bioinformatics databases and resources.
• Experience with automated reporting, workflow optimization, and computational quality control.
• Ability to interpret experimental findings and translate complex genomic analyses into actionable scientific recommendations.

Ideal Candidate Profile:

• An experienced bioinformatics or computational biology professional with hands-on NGS analysis experience.
• Strong in Python and/or R programming, genomic data analysis, and computational workflow development.
• Experienced in analyzing complex biological datasets, including RNA-seq, scRNA-seq, ATAC-seq, or multi-omics data.
• Able to integrate genomic and biological information to identify potential therapeutic targets and disease biomarkers.
• Familiar with Linux-based computational environments, bioinformatics databases, and reproducible analytical workflows.
• A collaborative problem-solver who can work effectively with computational biologists and experimental scientists.
• Capable of communicating scientific findings clearly and proposing innovative approaches to research challenges.