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Data Scientist

Remote, Remote · Information Technology
My client is looking for a Data Scientist.  This position is remote.  The duration of this project is 6 months. 

Skills Required :
Must haves:
  • Experience with large datasets in distributed environments
  • Strong statistical application experience (application in healthcare preferred)
  • Good experience in utilizing Data using SQL and other data pipelines
  • Machine Learning, NLP experience
  • Hands-on with Python, SAS, or R analytics tools/language
  • Healthcare background preferred ( Molecular Microbiology, Pathobiology, BioInformatics, Molecular Pharmacology etc.)
Requires training in fields such as engineering, statistics, mathematics, economics or similar vocations generally obtained through completion of a four-year bachelor’s degree. Strong problem-solving and analytical skills with experience in statistical modeling is preferred. Proficient with Excel, Python/R , SAS and Databricks preferred. Requires a minimum of one (1) to two (2) years’ experience as a Data Scientist.
  • Strong analytical, problem solving, and modeling skills to evaluate business problems and apply applications knowledge to identify appropriate solutions
  • Proficient in SAS or Python or R data analytics tools as well as Microsoft SQL query tools.
  • Understanding of Machine Learning operations management or experience with Databricks MLflow.
  • Designs experiments, test hypotheses and builds analytic models.
  • Deep knowledge of NLP text mining especially information extraction from clinical data
  • Deep knowledge of healthcare informatics and/or information management
  • Experience working with domain ontologies such as ICD9 & 10, MeSH, MedRA, RxNorm, SNOMED CT
  • Familiarity with healthcare and life science information (e.g. EHRs)
  • Conducts data analysis and designs and develops moderately complex analytic algorithms.
  • Validates analysis by comparing appropriate samples.
  • Employs the appropriate algorithm to discover patterns.
  • Experience with state-of-the-art techniques in machine learning algorithms, including deep neural networks, NLP, dimensionality reduction, ensemble methods, graph algorithms

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