Associate Manager, Statistical Genetics (Applied Bioinformatics Scientist)

What you'll do

• Conduct genetic association analyses including GWAS, EXWAS, Mendelian randomization, and polygenic risk score modeling.
• Integrate large-scale genetic data with multi-omic datasets to discover and validate new therapeutic targets.
• Develop and implement methods for data harmonization and normalization across in-house and public resources.
• Apply functional genomic data to prioritize specific genes and variants of interest.
• Perform quality control on large-scale genetic and phenotypic datasets.
• Identify and investigate data-driven hypotheses within the scope of analytic and translational genetics.
• Design and independently execute analytical studies from conception to completion.

What we're looking for

• PhD degree required.
• 0-2 years of experience analyzing omics data and genetic association analyses using large-scale genetic data.
• Proficiency in multi-omic data integration for therapeutic target discovery.
• Experience developing and implementing data harmonization and normalization methods.
• Expertise in genetic analysis approaches including GWAS, EXWAS, rare variant analysis, Mendelian randomization, LD Score regression, polygenic risk score modeling, pleiotropy analysis, and meta-analysis.
• Strong programming skills in languages such as Python, R, C/C++, Bash, and/or Julia.
• Strong quantitative skills including applied statistical techniques like regression, classification, Bayesian inference, and hypothesis testing.
• Experience working with immunologic datasets or immunology is preferred.