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Senior Scientist; I​/II), Human Genetics Group

Job in Chicago, Cook County, Illinois, 60290, USA
Listing for: AbbVie
Full Time position
Listed on 2026-01-17
Job specializations:
  • Research/Development
    Research Scientist, Data Scientist
Job Description & How to Apply Below
Position: Senior Scientist (I/II), Human Genetics Group

Company Description Abb Vie’s mission is to discover and deliver innovative medicines and solutions that solve serious health issues today and address the medical challenges of tomorrow. We strive to have a remarkable impact on people's lives across several key therapeutic areas – immunology, oncology, neuroscience, and eye care – and products and services in our Allergan Aesthetics portfolio. For more information about Abb Vie, please visit us at  Follow @abbvie on X, Facebook, Instagram, You Tube, Linked In, Tik Tok.

Job Description

The Genomics Research Center within the Quantitative Medicine and Genomics organization at Abb Vie is seeking a talented and motivated Senior Scientist to join the Human Genetics team to support our target discovery and development efforts. This individual will contribute to studies aimed at novel target discovery and understanding the biological mechanisms of diseases of interest to Abb Vie. The ideal candidate will be detail-oriented and collaborate with cross-functional teams to design, interpret, and deliver genomic analyses that inform our pipeline.

This position is in North Chicago, IL with no remote option.

Key Responsibilities
  • Lead genetics-driven target and biomarker identification across Abb Vie’s therapeutic areas using cutting-edge methods and large-scale biobank datasets (e.g., Finn Gen, Alliance for Genomic Discovery, UK Biobank, All of Us) and clinical cohort data.
  • Design and execute innovative approaches to uncover genotype-phenotype associations through disease-focused case-control and time-to-event study designs.
  • Identify genetic determinants influencing disease progression and patient response to treatments.
  • Analyze polygenic risk scores (PRS) to enhance patient stratification, identify genetically defined subgroups, gain insights into disease mechanisms, and support precision medicine strategies.
  • Assess heterogeneity in disease risk and investigate how PRS profiles are associated with differences in treatment responses.
  • Systematically mine internal and external phenome-wide association study (PheWAS) datasets to identify novel and population-specific genetic associations.
  • Analyze genomics data from clinical trial participants to identify response biomarkers and support reverse translation efforts.
  • Perform and interpret post-GWAS analyses (e.g., fine mapping of GWAS loci, GWAS signal colocalization with molecular QTLs, Mendelian Randomization and others) to identify and prioritize causal genes and targets.
  • Integrate single-cell omics and proteomics datasets with genomic and clinical data.
  • Collaborate with therapeutic area scientists to generate therapeutic hypotheses, support novel target identification and validation through exploratory analyses, and facilitate progression through pipeline phase transitions.
  • Lead cross-functional projects with therapeutic area leads.
Required Qualifications
  • Bachelor’s Degree or equivalent education and typically, 10-12 years of experience, Master’s Degree or equivalent education and typically 8-10 years of experience, PhD and 0-4 years of experience.
  • Fluency in programming languages such as R and Python and working in command-line on HPC clusters.
  • Expertise in biobank scale genome-wide association studies (GWAS) and rare variant association studies (RVAS).
  • Hands‑on experience in methods and tools such as PLINK, SAIGE, REGENIE, fast

    GWA, SKAT/ACAT.
  • Hands‑on experience working with different types of genotype data such as array, WGS, and imputed.
  • Hands‑on experience with electronic health records (EHR) and OMOP CDM format data.
  • Familiarity with open‑source genomics and omics resources (e.g., Open Targets, HGMD, GTEx, eQTL Catalog and others).
Preferred Qualifications
  • Previous industry experience in pharmaceutical or biotechnology companies working with large-scale human genetic datasets.
  • Experience in cloud genomics research environments (e.g., All of Us Researcher Workbench, UK Biobank Research Analysis Platform and Finn Gen sandbox).
  • Strong track record of relevant scientific publications and presentations.
Additional Information
  • The compensation range described below is the range of possible base pay compensation that the…

Position Requirements
10+ Years work experience
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