Programmer - III*

RWD Programmer

As a member of the RWE Generation Innovation Unit, individuals will have access to real-world databases and act as the stewards of best practices, standards, and methodologies underlying the use of real-world data (RWD). The incumbent will design and conduct analyses of RWD to characterize patient cohorts and perform data visualization and QC datasets for use in downstream analyses. The RWD Programmer will conduct timely, relevant, and rigorous analysis of RWD to address critical questions on clinical operations strategy, as well as collaborate with epidemiologists and other scientists to develop, refine, and scale data management and analytics procedures, systems, workflows, best practices, and other issues.

Key Responsibilities

1. Co-develop analysis specifications, develop programs, and conduct analyses for descriptive epidemiology using RWD, including longitudinal claims, EHR, and registry (e.g., SEER).
2. Contribute to quality control of programs and automation of data refreshes.
3. Contribute to the selection of appropriate internal databases to characterize patient populations.
4. Develop and execute data visualization of patient populations.
5. Maintain timelines and progress reporting to stakeholders.
6. Curate phenotype algorithms and code lists for defining patient cohorts in RWD.

Knowledge, Skills, And Experience

1. Master’s degree in Biostatistics, Epidemiology, Data Science, Computer Science, or related discipline from an accredited institution, with a minimum of six (6) years of relevant, post-graduation experience.
2. Doctoral degree with a minimum of two (2) years of relevant experience. Direct experience in lieu of academic training is acceptable.
3. Formal training in programming and demonstrated proficiency in statistical analysis using R, SAS, and SQL. Familiarity with Python (including packages used for geographic visualization).
4. Strong track record of developing efficient, reusable code for real-world data (RWD) analyses used in pharmacoepidemiology.
5. Understanding of epidemiology and the application of RWD studies to characterize patient populations.
6. Deep understanding of the quantitative validation of phenotype definitions in RWD and the coding vocabularies (e.g., ICD, CPT, NDC) used to define variables in RWD.
7. Knowledge of US secondary data sources required; additional experience with international data sources is preferred.
8. Experience in observational research study design, execution, and communication a plus.
9. Planning and communicating results from descriptive RWD analyses, including claims and EHR, a plus.