Senior R Programmer/Analyst – RWD & Analytics

By | December 3, 2022
  • Contract
  • Remote

SimulStat

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Remote, 12-month renewable contract   

Description
As a Sr programmer/analyst, Real-World Data and Analytics, you will conduct hands-on programming (expert level in R, proficient in SQL) in supporting our real-world data & analytics needs under the supervision of our Director HEOR analytics scientists.  

Responsibilities:

  • Respond to HEOR Director’s request timely
  • Understand query, analytics requests, and study specifications
  • Proactively clarify requests and ensure accurate implementation of protocols and analytical specifications
  • Conduct queries to real-world data in OMOP Common Data Model (CDM)
  • Create code mappings (e.g., ATC to NDC) using OMOP vocabularies to support HEOR’s needs
  • Support analytical methods using R where needed (e.g., certain advanced methods requiring R packages)
  • Ensure high-quality work products
  • Keep detailed documentation and generate results with a clear and professional presentation
  • Detail-oriented with excellent communication skills.
  • Can work independently and efficiently to meet aggressive timelines where needed
  • Adapt to rapidly changing priorities

Qualifications and Experience Required:

  • A Master’s degree in health services research, epidemiology, biostatistics, public health, or a subject area with a strong focus on the application of data science to healthcare data with 3+ years of hands-on programming experience; or a Bachelor’s degree in a quantitative field with 7+ years of hands-on programming and analytic experience using healthcare data.
  • Expert R programmer and proficient at SQL
  • Expert knowledge of OHDSI OMOP CDM, vocabularies, and its use in real-world evidence generation
  • Hands-on experience in using various OHDSI open-source tools, such as HADES R packages, OHDSI Shiny, as well as Atlas tool, to conduct real-world research
  • Ability to revise and develop R packages to fit custom study needs
  • Proficiency with common statistical methods, such as survival analysis, generalized linear models
  • Familiarity with various observational study designs, such as cohort, case-control, cross-sectional
  • Ability to effectively communicate methods and findings
  • Knowledge of visualization software is a plus

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