Job: Scientist (Genomics Data Analytics) at Omicsoft, Cary, North Carolina, USA
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gravatar for Istvan Albert
4.7 years ago by
Istvan Albert ♦♦ 81k
University Park, USA
Istvan Albert ♦♦ 81k wrote:

Scientist (Data Analytics) 
Omicsoft - Cary, NC

http://www.indeed.com/job/scientist-data-analytics-ebc435a903fe1277

Job Description:
We are seeking a talented and motivated scientist to join the Scientific Data Analytics Team at Omicsoft. This position will be based in Cary, North Carolina with the primary responsibility to develop data analysis plans/pipelines for public high-throughput genomics data from varied disease areas. By collaboratively working with internal researchers and software development team, the successful candidate will integrate acquired knowledge into our efforts to build a strong analytic pipeline to process large scale genomics data-sets and developed innovative technology to deliver high-throughput data in a user-friendly fashion.

Contact:
Please email hr AT omicsoft DOT com

Responsibilities:
Responsibilities of this position include, but are not limited to,
Review the scientific publications, protocols or other documentation to evaluate study aims, design, methods and research findings, and documents these information accordingly.
Download, QC, annotate, and analyze high-throughput datasets from various sources; properly summarize and interpret the analysis outcomes to clients.
Work closely with software developers to design, test and manage the data auto-curation and analytical pipeline.

Qualifications:
Successful applicants should be detail-oriented and have good communication skills. This includes past work performance and/or assignments requiring active interaction with researchers, analysts, IT staff, and end users.
PhD or Master's degree (applicants with master's degree must have 2+ years of related working experiences) in bioinformatics, computational biology or biostatistics.
Must have prior experiences analyzing microarray and/or next generation sequencing data.
Must have good knowledge of statistical modeling using R or SAS.
Familiar with current trend of clinical and academic research in immunology, human genetics and biomedical medicine.

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