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Senior R Programmer/Analyst - RWD & Analytics (REMOTE) (Science & Biotech)
Homebased, NY 10591
Recruited by: Ali Henderson | Recruiter | SimulStat Inc. See all my Jobs

  • Hiring Company: Simulstat's client
  • Industry: Science & Biotech
  • Compensation: Depends On Experience
  • Expires: Feb 14, 2023
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Job Description

Must haves: a strong R programmer with extensive experience in the OHDSI OMOP common data model. He/she should also be well-versed in RWD/RWE research, Remote 12 month contract
Remote, 12-month renewable contract

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.

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