Master's degree or PhD in epidemiology, biostatistics, statistics, bioinformatics, or economics with 5+ years of RWE analytics experience in pharma, CRO, or academia.
Intermediate to expert proficiency in SQL is essential; SAS or R proficiency is required.
Deep expertise in analyzing RWE data sources like Optum, Truveta, and UK Biobank, including clinical trial or registry data analysis.
Familiarity with relational databases and understanding of claims and ancillary file layouts.
Experience in applied statistics, regression analysis, survival analyses, and propensity weighting.
Strong project management skills to handle multiple tasks efficiently.
Excellent communication skills for effective stakeholder engagement.
Responsibilities
Assist in developing study protocols and analysis plans using large RWD sources.
Liaise with data vendors to ensure relevant data extracts align with study protocols.
Create analytical databases from data extracts to facilitate data analysis.
Conduct analyses per methods detailed in study protocols and analysis plans.
Produce tables and figures for discussions with stakeholders and in study reports.
Present results internally and to clients effectively.
Assist in preparing study reports and other deliverables.
Potentially supervise other team members in the future.
Benefits
Opportunity to work on impactful research studies with real-world data.
Collaboration with a multidisciplinary team of epidemiologists and statisticians.
Access to continuous professional development and training opportunities.
Strong focus on innovation in data standardization and visualization.
Potential for career progression in a dynamic work environment.
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
