Senior Epidemiological Programmer, Real World Evidence - FSP

IQVIA•Durham, NC
•$88,300 - $220,900

About The Position

IQVIA is expanding its dedicated Real World Evidence (RWE) FSP team, which works fully within the environment of a prominent pharmaceutical company. This role sits within the Real World Solutions team and leads development of datasets and longitudinal analyses for observational studies in the virology therapeutic area under one client portfolio. The programmer applies expertise in observational research using EMR and claims data, statistical programming, epidemiological study design, cohort building, and RWE outcome measures, while managing multiple studies and complex analyses. The role also provides access to real-world databases and stewardship of the client’s best practices, standards, and methodologies for using real-world data (RWD).

Requirements

  • Master’s degree in Biostatistics, Epidemiology, Outcomes Research, or a related field with 5–8 years of relevant experience, or a PhD with 3 years of relevant experience.
  • Strong track record analyzing real-world data using EMR and claims data.
  • Proficiency in advanced statistical programming using SAS and/or R, macros, and SQL.
  • Demonstrated experience and applied proficiency in RWE study design, terminology, cohort building, and analytic methodologies.
  • Prior pharmaceutical or CRO experience.
  • Excellent analytical and communication skills, with attention to detail.
  • Ability to effectively manage and prioritize multiple tasks and projects.

Responsibilities

  • Lead development of analytic datasets by processing raw data and conducting data checks and cleaning with secondary real-world data sources, including claims, EHR, and laboratory data.
  • Assess the feasibility of real-world data sources to characterize patient populations, build patient cohorts, and define and validate study-specific variables.
  • Conduct and quality-check analyses, including identifying diagnosis and treatment codes and applying statistical methods to address censored data, confounding, differing person-time, and missing data.
  • Collaborate with epidemiologists on study design and methodology and define specifications for descriptive and complex statistics, including longitudinal analysis, survival analysis, regression models, and propensity score methods.
  • Develop and quality-check tables, figures, and listings (TFLs) for protocols, reports, and manuscripts using RWD such as claims and EHR data.
  • Support development of study documents, including protocols, statistical analysis plans, and study reports.
  • Communicate timelines, progress reports, and results to project teams and key stakeholders.
  • Provide technical, programming, statistical, and epidemiological expertise and independently bring solutions to teams working on complex studies.

Benefits

  • Health and welfare benefits may be offered, depending on the position.
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