Senior Programmer analyzing real-world healthcare data for a pharmaceutical company’s epidemiology studies. Developing analytical databases, conducting statistical analyses, and presenting research findings.
Responsibilities
Provide support to the Epidemiology team by preparing Real World data, advising on data analytic strategies, and supporting stakeholders in epidemiology analytic activities
Program and conduct statistical analysis under the direction and supervision of epidemiologists/statisticians, including data coding, algorithm creation, dataset linkage, and use of statistical packages or platforms
Support statistical programming for data standardization, visualization, and reporting of observational data
Support Medical Affairs, Global Patient Safety and Risk Management, and Clinical Development activities involving RWD and observational studies
Partner with Epidemiologists to manage relationships with internal and external stakeholders
Prioritize and manage work across multiple projects and stakeholders
Provide strong communication for successful and timely project delivery
Solve technical problems using experience and expertise
Assist in developing study protocols and analysis plans leveraging large RWD sources (Claims and/or EHR)
Liaise with data vendors to obtain relevant data extracts
Create analytical databases from data extracts
Conduct analyses according to study protocols and analysis plans
Produce tables and figures for investigators, clients, and study reports
Present results internally and to clients
Assist in preparing study reports and other deliverables
May have supervisory responsibilities in the future
Requirements
Master’s degree or PhD in related field (epidemiology, biostatistics, statistics, bioinformatics, economics) and 5+ years of experience conducting RWE analytics for pharma industry, CRO, or academic institution
Intermediate to expert level proficiency in SQL is a must. In addition, SAS or R proficiency is required
Deep expertise analyzing RWE data sources such as Optum (Clinformatics Datamart® and Market Clarity), Truveta and UK Biobank
Experience analyzing clinical trial and/or registry data is required
Familiarity with relational databases and proficient understanding of claims and ancillary file layouts
Experience with applied statistics including regression analysis (OLS, longitudinal, logistic, Cox, GLM/GEE), survival analyses (Kaplan-Meier, cumulative incidence, accelerated failure time models), and propensity weighting
Excellent project management skills; can prioritize multiple tasks and goals to ensure timely completion
Confident and competent when interacting with internal and external stakeholders
Strong written/verbal communication skills. Highly effective at summarizing and presenting key considerations and evidence
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