Aliz Raksi is a Staff Bioinformatics Scientist with a decade of experience turning high-throughput sequencing and multi-omics data into actionable insights for clinical and research settings. She has deep expertise in NGS, optical genome mapping, variant interpretation, and biomarker discovery, and has built and validated production pipelines for clinical sequencing at scale. Comfortable from low-level C++ to high-productivity Python/R workflows, she pairs strong statistical and machine-learning skills (Bayesian inference, MCMC, PCA) with cloud and HPC production experience (AWS, DNAnexus, SGE, Docker). Her work spans discovery—exome and genome mining for complex disease genetics—to clinical translation, including neoantigen discovery and GLP/CLIA-aligned sequencing workflows. A marathon finisher and world traveler, she brings persistence and cross-disciplinary communication to teams that bridge biology, software engineering, and clinical impact.
Contributions:16 commits, 15 pushes, 1 branch in 4 months
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