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Remote Clinical Epidemiology SAS programmer (OMOP and/or Hadoop trained or experience) (Science & Biotech)
Remote, NC 27513
Recruited by: Ali Henderson | Senior Recruiter | SimulStat Inc. See all my Jobs

  • Hiring Company: SimulStat's client
  • Industry: Science & Biotech
  • Compensation: Hourly
  • Expires: Apr 28, 2020
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Job Description

The senior statistical programmer position will be responsible for manipulating large databases and generating reports using SAS to enable analysts to explore real world healthcare data assets. Candidates must have excellent SAS programming skills and the ability to implement complex data step logic. Candidates must be comfortable with creating complex analysis data sets derived from various data sources with a careful eye for outliers and errors. Prior experience with large databases and observational research methods such as epidemiology and statistical methods is strongly desired. Experience in designing and building standard reporting packages and analysis tools also highly desired.

Strong communication, time management, enthusiasm and documentation skills are essential in this home-based position.

Basic Qualifications

Bachelor’s degree in Computer Science, Statistics, Mathematics, or other subject with high statistical content
Minimum four years SAS statistical programming experience
Database programming using SQL or experience with advanced statistical methods such as survival and regression
Experience with real world healthcare data such as DRG, MarketScan, Optum, PharMetrics, Medicare and EMR databases

Preferred Qualifications

Master’s degree in Epidemiology, Biostatistics, Computer Science, or other subject with high statistical content
Training or experience using the OMOP common data model
Training or experience with the Hadoop database platform and Impala or Hive SQL
Pharmaceutical/Biotech industry experience
Spotfire, Tableau, or other data visualization experience
Understanding of genetic and biomarker research and or statistical genetics
Familiarity with publicly available genetic databases such as TCGA or UK Biobank