Data Analyst II Job at Spectraforce Technologies in Chicago

Job Title: Data Analyst II
Duration: 12 Months
Location: Remote

• Genomic and multi-omic data analysis, including advanced analyses of single-cell RNASeq, bulk RNASeq, and preferably spatial transcriptomics. Familiarity with statistical approaches in omics.
• Fluency in Python and/or R; working in Linux environments; familiarity with workflow management (Nextflow), version control.
• Excellent organizational, communication, collaboration, and interpersonal skills.
• Experience in immunology or fibrotic diseases, especially MASH, is a plus.
• Educational background: Masters with 3-5 years, PhD 0-3 years of experience.

Job description:

Bioinformatics for Immunology, Genetic and Genomic Sciences (BIGGS) team under the umbrella of Quantitative Medicine and Genomics (QM&G) performs computational research and provides data-driven insights for the immunology discovery and translational programs.

The team is seeking a talented, creative, and motivated individual for a contractor position to perform data integration and analysis of bulk transcriptomics, single-cell omics, and available spatial transcriptomics datasets in an immunology-related disease area, with a focus on liver biology and metabolic-associated liver disease.

The candidate will work in close collaboration with members of BIGGS, Immunology Discovery, and Specialty Development teams to perform omics data curation, integration, and computational analysis.

The successful applicant will employ and develop computational tools and algorithms, integrate and analyze complex multi-omic and single-cell datasets to enable a comprehensive understanding of the disease. Familiarity with the best practices and cutting-edge tools in single-cell analysis is preferable. The results will drive target validation and in-depth understanding of disease biology, with a direct impact on discovery and translational programs.

Key responsibilities

• Systematically QC, annotate, and integrate public omics and single-cell datasets.
• Perform downstream analyses on the integrated datasets; employ cutting-edge tools and analytical approaches to advance the understanding of liver disease biology.
• Contribute easily maintainable, robust, and flexible code for analysis pipelines.
• Interpret and communicate results to the wider scientific team.

Interviews

• Initial screen with manager. 1-2 additional panel interviews

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