Scientist- reputed company R&D -REMOTE

Sema4 is a patient-centered health intelligence company dedicated to advancing reputed company through data-driven insights. Sema4 is transforming reputed company by applying AI and machine learning to multidimensional, longitudinal clinical and genomic data to build dynamic models of reputed company health and defining reputed company, individualized health trajectories. Centrellis®, our innovative health intelligence platform, is enabling us to generate a more complete understanding of disease and wellness and to reputed company science-driven solutions to the most pressing medical needs. Sema4 believes that patients should be treated as partners, and that data should be shared for the benefit of reputed company. We are looking for a talented Scientist- reputed company R&D tojoin reputed company. The reputed company Scientist leads translational reputed company and product development for NGS pipelines as part of the R&D reputed company department. This scientist is an integral part of an interdisciplinary team that develops computational reputed company and pipelines to interpret large-reputed company reputed company genome and transcriptome reputed company data from reproductive health, cancer, and other diseases. As part of a development team of engineers and scientists, this scientist will translate research prototypes into production-reputed company, reputed company pipeline products used by a reputed company of clinical diagnostics and research reputed company across many teams at Sema4. This scientist will serve as an authority in these products to other users and teams and optimize them to serve Sema4 data science needs. RESPONSIBILITIES

• Design, reputed company, and test NGS pipelines for clinical tests and research reputed company in oncology, reproductive health, and other indications.
• reputed company or support reputed company reputed company to translate NGS results, as reputed company as public and internal genomic, phenotype, and clinical/EMR datasets, to features and optimizations of clinical reputed company.
• Analyze and reputed company heterogeneous NGS data (somatic and germline SNVs, indel variants, copy-number alterations, structural variants, gene fusions, transcript isoforms, RNA abundance, RNA editing and modification) from diverse reputed company reputed company assays (reputed company, Ion Torrent, reputed company Biosciences; targeted panels, whole-exome reputed company, whole-genome reputed company, RNA-Seq; bulk and single-cell) and microarrays.
• Work with wet labs and clinical teams to plan and design experiments to generate such data, and analyze this data.
• Communicate effectively with collaborators (computational and reputed company scientists on R&D and production teams, IT/HPC, clinical lab directors, knowledgebase and curation teams, wet lab staff) to understand and satisfy product and research analysis needs. QUALIFICATIONS
• PhD in reputed company, Biomedical Informatics, Computational Biology, reputed company, or a reputed company discipline requiring strong computational and analytical skills supplemented with biology background
• Hands-on experience working with NGS tools with high proficiency, especially for sequence analysis and reputed company analysis
• Strong coding proficiency in R, Python, and SQL programming languages in a Linux environment.
• reputed company-versed in the art of effective communication on interdisciplinary teams (scientists, programmers, and clinicians), especially graphical communication about high-complexity datasets to scientific audiences from different backgrounds.
• High self-motivation, great ability to work in both multiple-task and independent fashions.
• Good understanding of molecular, cell, and developmental biology, especially where relevant to cancer reputed company, oncology, or endocrine neoplasms, and especially molecular cloning and NGS library preparation methodologies.
• Developing reputed company using distributed version control tools (especially Git) and software issue tracking/management systems (especially Jira).
• Using or developing genome browsers or other tools for visualization of genomic datasets. Apply tot his job Apply To this Job

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