Computational Scientist - Human Genetics - Remote

This is a remote position. Our Client, a world leader in Biotechnology is looking for a " Computational Scientist - Human Genetics - Remote " for SSF, CA Job Duration: Long Term Contract (Possibility Of Extension) Pay Rate: $56/hr on W2 ​ Company Benefits: Medical, Paid Sick leave, 401K ​ The Human Genetics department is seeking a highly independent Computational Scientist with hands-on experience in genetic epidemiology, statistical genetics, computational biology, or bioinformatics . The role will focus on developing and applying analytical approaches to integrate and interpret genetic, genomic, and clinical data , including large-scale sequencing and single-cell datasets. The scientist will contribute to multimodal data integration, machine learning, and translational research to generate insights into disease biology. Key Responsibilities • Analyze large-scale genetic, genomic, and clinical datasets from internal studies, clinical trials, high-throughput screens, academic collaborations, industry partners, and public datasets. • Develop computational and statistical approaches to integrate and interpret complex biological datasets. • Analyze whole genome sequencing, RNA-Seq, scRNA-Seq, scATAC-Seq, and other molecular assay data . • Develop and apply multimodal data integration methods to connect genetic, molecular, clinical, and imaging data. • Implement machine learning algorithms to identify associations between imaging and omics datasets. • Coordinate the intake, preparation, quality control, and organization of new datasets. • Document analytical workflows, code, methods, findings, and results. • Present scientific findings to Human Genetics teams and cross-functional collaborators. • Contribute to scientific publications and translational research initiatives. Required Qualifications • PhD, or Master's degree with significant relevant experience, in Statistical Genetics, Computational Biology, Bioinformatics, Genetic Epidemiology , or a related field. • Extensive experience analyzing large-scale genetic/genomic datasets. • Knowledge of genetic epidemiology and statistical genetics . • Experience with GWAS and association analysis using array- or sequence-based human genetic data. • Experience analyzing RNA-Seq, single-cell sequencing, and/or proteomic data . • Experience integrating genetic and molecular datasets for multimodal analysis . • Strong programming skills in R, Python, and shell scripting . • Experience with Git and high-performance computing environments such as SLURM . • C++ experience is a plus. • Ability to work independently, make sound analytical decisions, meet deadlines, and produce high-quality results with minimal supervision. If interested, please send us your updated resume at / Originally posted on Himalayas