Xenon7 is an inferno where skill, dedication and passion run together.
About our client:
Global healthcare leader headquartered in Indianapolis, Indiana. The Cardiometabolic Research (CMR) Therapeutic Area of our client, focuses on the discovery of biologic, small molecule and genetic therapeutics for the treatment of cardiometabolic diseases and associated complications.
We are seeking a Statistical Geneticist with expertise in whole genome sequencing (WGS), proteomics, and clinical outcomes analysis to advance our research in identifying novel therapeutic targets. This role will involve analyzing large-scale biobank and population-cohort datasets to uncover genetic and molecular factors associated with disease risk, progression, and treatment response. You will operate as part of the CMR Data Science and Computational Biology (DSCB) team and partner with early discovery scientists and clinicians, translational scientists, bioinformaticians and geneticists.
Key Responsibilities
Apply statistical and computational approaches to analyze WGS/WES, proteomics, metabolomics, and clinical data for biomarker discovery
Conduct rigorous analyses of large-scale population cohorts and biobank datasets to identify genetic variants and causal genes associated with disease outcomes
Develop and implement machine learning and bioinformatics pipelines to integrate multi-omics data
Collaborate with interdisciplinary teams, including geneticists, epidemiologists, and clinicians, to interpret findings and guide therapeutic development
Prepare scientific reports, presentations, and publications detailing research outcomes
Contribute to the development of novel statistical methods for analyzing high-dimensional biological data
Requirements
Qualifications & Requirements
PhD in statistical genetics, bioinformatics, computational biology, biostatistics, or a related quantitative field
Qualified applicants must be authorized to work in the United States on a full-time basis
Additional Skills/Preferences
Expertise in whole genome and whole exome sequencing analysis, proteomics, metabolomics and other molecular data analysis, and clinical outcomes research
Strong proficiency in statistical modeling, machine learning, and high-dimensional data analysis
Experience working with large biobank and cohort datasets (e.g., UK Biobank, All of Us, FinnGen)
Proficiency in programming languages such as R, Python, and SQL for data analysis
Familiarity with genetic association studies, GWAS, and polygenic risk scores
Excellent communication and collaboration skills to work effectively in cross-functional teams
Experience in pharmaceutical or biotech industry settings
Knowledge of functional genomics and multi-omics data integration
Strong publication record demonstrating contributions to statistical genetics and biomarker discovery and analysis
Prior experience in cardiometabolic research
Prior experience with polygenic risk score models
This is an exciting opportunity to advance precision medicine and therapeutic target identification through innovative statistical genetics approaches. If you are passionate about employing big data for scientific discovery, we encourage you to apply!
Benefits
Attractive, market-leading salary package
Clear career advancement path with professional development opportunities
Seniority level
Internship
Employment type
Contract
Job function
Other
Industries
IT Services and IT Consulting
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