About the role

Senior Statistical Programmer supporting a pharmaceutical client’s epidemiology team with real-world evidence data preparation and statistical analysis. Developing analytical databases, study outputs, and reports from claims and EHR data.

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 analyses under epidemiologist/statistician supervision, 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 through observational studies, background-rate analyses, regulatory/safety documents, and patient population or protocol feasibility assessments
Partner with Epidemiologists to manage internal and external stakeholder relationships
Assist in developing study protocols and analysis plans using large claims or EHR real-world data sources
Liaise with data vendors to obtain relevant research-study 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 with study reports and other deliverables
Prioritize and manage work across multiple projects and stakeholders
Solve technical problems and support successful, timely project delivery
May have supervisory responsibilities in the future

Master’s degree or PhD in a related field such as epidemiology, biostatistics, statistics, bioinformatics, or economics
5+ years of experience conducting real-world evidence analytics for a pharmaceutical company, CRO, or academic institution
Intermediate to expert proficiency in SQL
Proficiency in SAS or R
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 desirable
Familiarity with relational databases
Proficient understanding of claims and ancillary file layouts
Experience with applied statistics, including OLS, longitudinal, logistic, Cox, GLM/GEE, Kaplan-Meier, cumulative incidence, accelerated failure time models, and propensity weighting
Excellent project management skills and ability to prioritize multiple tasks and goals
Confidence and competence interacting with internal and external stakeholders
Strong written and verbal communication skills
Ability to summarize and present key considerations and evidence effectively