Master's or PhD in epidemiology, biostatistics, statistics, bioinformatics, or economics with 5+ years in RWE analytics within pharma, CRO, or academia.
Intermediate to expert SQL proficiency, with requirements for SAS or R.
Deep expertise with RWE data sources like Optum, Truveta, and UK Biobank; clinical trial and registry data experience.
Familiarity with relational databases and claims file structures.
Experience with applied statistical methodologies including regression, survival analyses, and propensity weighting.
Strong project management abilities with a capacity to juggle multiple tasks and deadlines.
Excellent communication skills for effective interaction with stakeholders.
Responsibilities
Assist in developing study protocols and analysis plans using large Real World Data sources.
Liaise with vendors to acquire relevant data extracts for research studies.
Create analytical databases to facilitate data analyses from these data extracts.
Conduct analyses according to study protocols and analysis plans.
Produce tables and figures for discussions and study reports.
Present analytical results to internal and external audiences.
Assist in preparing study reports and deliverables.
Potential future supervisory responsibilities.
Benefits
Collaborative work environment with a focus on innovation and data strategy.
Engagement in diverse projects across pharmaceutical disciplines.
Opportunities to develop expertise in Real World Data applications in health research.
Professional growth with potential supervisory roles in the future.
Access to cutting-edge tools and methodologies in epidemiology.
Full Job Description
Job Description
You will contribute by:
Providing support to the Epidemiology team by preparing Real World data, advising on data analytic strategies, and supporting stakeholders in various epidemiology analytic activities
Programming and conducting statistical analysis under the direction and supervision of epidemiologists/statisticians including data coding, creation of algorithms, linkage of datasets, and use of statistical packages or platforms
Supporting statistical programming to generate innovative means of data standardization, visualization, and reporting of observational data
Supporting Medical Affairs (e.g. observational studies leveraging RWD); Global Patient Safety and Risk Management (e.g., analysis to obtain background rates) for the development of regulatory/safety documents, and Clinical Development (e.g.; assessment of patient populations/ protocol feasibility)
The position will partner with Epidemiologists to manage relationships with internal and external stakeholders
Being able to prioritize and manage work across multiple projects and stakeholders
Providing strong communication to ensure successful and timely project delivery
Solving technical problems with experience and expertise
Responsibilities
Summary of Key Responsibilities:
Assist in development of study protocols and analysis plans leveraging large RWD sources (Claims and/or EHR)
Liaise with data vendors to obtain relevant data extracts for research studies consistent with study protocols
Create analytical databases from data extracts to facilitate conduct of data analyses
Conduct analyses consistent with methods set forth in study protocols and analysis plans
Produce tables and figures for discussions with other investigators, clients, and for study reports
Present results internally and to clients
Assist in the preparation of study reports and other deliverables
May have supervisory responsibilities in the future
Qualifications
What we're looking for:
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 Datamart4 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
