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

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