New

Data Analyst II

Spectraforce Technologies
United States, Illinois, Chicago
Sep 08, 2025
Job Title: Data Analyst II Duration: 12 Months Location: Remote What are the top 3-5 skills, experience or education requited for this position: 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, 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 include: 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