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Data Technical Analyst; RWD

Job in Rahway, Union County, New Jersey, 07065, USA
Listing for: Creative Solutions Services, LLC
Full Time position
Listed on 2026-06-14
Job specializations:
  • IT/Tech
    Data Analyst, Data Scientist, Data Security
  • Research/Development
    Data Scientist
Salary/Wage Range or Industry Benchmark: 80000 - 100000 USD Yearly USD 80000.00 100000.00 YEAR
Job Description & How to Apply Below
Position: Real-World Data Technical Analyst (RWD)

Job Description

The Observational and Real-World Evidence (CORE) Real-World Data Analytics and Innovation (RDAI) team is seeking a Real-World Data (RWD) Technical Analyst to support real-world evidence generation and oncology outcomes research. This role will work with epidemiologists, biostatisticians, and scientists to conduct analyses using real-world data sources (claims, EHR/EMR, registries) and help develop advanced analytics tools and methodologies that accelerate observational research.

Responsibilities
  • Conduct feasibility analyses using internal real-world datasets (claims, EHR/EMR) to support oncology outcomes research.
  • Execute end-to-end study analyses using platforms such as RStudio and SAS Studio.
  • Support development and implementation of analytics methods and tools to address confounding in observational healthcare data.
  • Perform targeted literature reviews to support study design and methodology.
  • Develop and maintain programming documentation, code specifications, and version control.
  • Generate analytic outputs and reports supporting real-world evidence studies.
  • Collaborate with cross-functional scientists to translate research questions into reproducible analytic workflows.
Requirements
  • Experience working with real-world healthcare data (claims, EHR/EMR, registries).
  • Strong understanding of epidemiologic or statistical methods for observational research.
  • Proficiency in R, SAS, and SQL (Python a plus).
  • Experience with R ecosystem tools (RStudio Workbench, RStudio Connect, RShiny).
  • Familiarity with survival analysis methods and packages (e.g., survival).
  • Experience working with databases (e.g., Redshift, MySQL).
  • Experience with version control tools such as Git.
  • Strong documentation, communication, and collaboration skills.
  • Experience supporting life sciences or pharmaceutical research environments.
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