Medical Analytics, Contractor (RWE Data Scientist) at Pharmaceutical Company in New York, New York, United States —
- Pharmaceutical Company
- New York, New York, United States USA
- 12/1/19 2019-12-01
Job ID: 1361922
Serve as the RWE data scientist and statistical programmer to supportproduct(s) and projects, with guidance and/or direct supervision from senior Medical Analytics and HEOR colleagues.
Plan and Execute Statistical Analyses
- Author parts of and/or provide significant input into the Statistical Analysis Plan (SAP) using large,
- real-world datasets to comprehensively and unambiguously define the statistical analysis specifications, data derivations, and display shells to be generated in collaboration with key stakeholders.
- Perform statistical analyses using a RWE analytics platform, SAS and/or R to create analytic datasets, generate tables, listings, and figures for internal use as well as in presentations and publications.
- Ensure quality of deliverables through appropriate testing/validation and active review for completeness and accuracy (including developing and implementing a well-documented validation plan).
Analyze RWE Data Sources
- Analyze large real-world data sources such as administrative claims databases (e.g. Truven Marketscan, Medicare, Medicaid), EHR data (e.g. Optum Humedica, Geisinger EHR data), survey data (e.g. NHANES, MEPS), and registries.
RWE Data Science and Statistical Programming
- Implement statistical methods (e.g. logistic regression, propensity scores, survival analysis, longitudinal mixed models) used to answer epidemiological, health-services, and HEOR questions
- Create analytic datasets by querying the large, real-world database
- Derive new variables using medical/diagnostic coding systems (e.g. ICD-9/ICD-10, CPT-4, HCPCS, Loinc codes) and complex algorithms (e.g. diagnosis codes and drug codes)
- Develop flexible and robust SAS macros to efficiently implement commonly-used methods or approaches
- Experience in authoring parts of and/or providing significant input in SAPs using large, real-world datasets, implementing the SAP using SAS or R, ensuring quality via validation, and explaining implementation details to technical and non-technical audiences.
- Experience in statistical programming methods as it relates to: real-world evidence generation in epidemiology, health-services research, and HEOR
- MS/MPH in statistics/biostatistics/epidemiology or related discipline (see Educational Requirements/Experience for more information)
- Expert knowledge of statistical programming methods using SAS or R to solve statistical problems.
At least 3 years of statistical programming experience with SAS or R working with large, real-world databases in the biotechnology, pharmaceutical or other healthcare industries.