Remote Scientist III – Computational Biology / Bioinformatics

Location: Remote | Client: Boehringer Ingelheim | 12-Month Contract

Sigma Systems is currently seeking a Remote Scientist III – Computational Biology/Bioinformatics to support oncology drug discovery research with our client, Boehringer Ingelheim. This remote contract opportunity is ideal for a highly skilled computational scientist with expertise in bioinformatics, multi-omics data analysis, genomics, and data-driven approaches to advance cancer therapeutics.

Job Summary:

The Remote Scientist III will join the Computational Innovation team and contribute to oncology drug development by applying computational science, bioinformatics, and advanced data analytics approaches. The successful candidate will analyze complex biological datasets, develop innovative computational methods, and collaborate with scientists and biologists to generate insights that support drug discovery programs.

Key Responsibilities:

• Support oncology drug discovery and development efforts through computational and data-driven approaches.
• Analyze multi-modal omics datasets to generate meaningful biological insights.
• Process and analyze publicly available and internally generated biological datasets using statistical and bioinformatics methods.
• Develop and apply innovative analytical approaches when standard methods are not sufficient.
• Collaborate with biologists and cross-functional research teams to solve complex scientific challenges.
• Research and apply emerging technologies in computational biology and data science.
• Stay current with scientific literature and emerging methodologies in oncology research.
• Perform biological pathway analysis and interpretation of computational results.
• Present findings and analytical insights to scientific collaborators and stakeholders.
• Maintain FAIR data principles with clear documentation, reproducibility, and data integrity.
• Support reproducible computational workflows and scientific best practices.

Required Qualifications:

• PhD degree from an accredited institution in Computational Sciences or a related scientific discipline, including:
  • Computer Science
  • Computational Biology
  • Genomics
  • Biostatistics
  • Bioinformatics
  • Biological Sciences
• Strong programming experience with:
  • Python
  • R
• Experience performing bioinformatics data analysis in Unix/Linux environments.
• Experience working with:
  • Bulk RNA sequencing (bulk NGS) data
  • Single-cell NGS data
• Experience analyzing complex biological datasets and generating scientific insights.
• Experience working with high-performance computing (HPC) clusters.
• Strong understanding of biological pathway analysis.

Preferred Qualifications:

• Experience in oncology or immunology research.
• Experience with:
  • Spatial transcriptomics
  • DNA methylation analysis
  • Liquid biopsy data analysis
• Familiarity with public oncology datasets and resources, including:
  • TCGA
  • GTEx
  • Human Cell Atlas
  • CZ CELLxGene
  • Human Tumor Atlas Network
• Experience applying machine learning or advanced analytics methods in biomedical research.
• Strong scientific communication and presentation skills.

Ideal Candidate Profile:

• PhD-level computational scientist with a strong background in bioinformatics.
• Passionate about using data science to accelerate cancer research and drug discovery.
• Comfortable collaborating with multidisciplinary scientific teams.
• Strong problem-solving skills with the ability to develop innovative computational solutions.