Description
The Senior Associate, RWD Analyst is responsible for supporting Fortrea's Real-world Evidence (RWE) services through successful delivery of complex analyses of data generated from global prospective and retrospective observational studies or existing secondary data sources. The role involves providing programming for the analysis of RWD from diverse sources, developing analysis-ready datasets, and creating tables/figures/listings (TFLs) from analytic datasets.
Responsibilities:
- Provide programming for the analysis of RWD from diverse sources including observational studies and existing secondary data sources
- Develop analysis-ready datasets from source data, including derivation of analytic variables, following an analytic plan
- Independently develop tables/figures/listings (TFLs) from analytic datasets and following an analytic plan
- Provide programs to validate analysis datasets and results presented in TFLs and resolve discrepancies with minimal oversight
- Create and maintain documentation of programming for assigned deliverables
- Provide quality cross-checks of written deliverables to analytic results
- Communicate accurate and timely status updates to RWE biostatisticians, epidemiologists, and team members
- Provide analytic programming of other data sources for various projects, as needed
Process Improvement:
- Follow standard operating procedures (SOPs) relevant to assigned projects
- Identify opportunities to enhance productivity, quality, and efficiency in analytic processes
People:
- Provide informal guidance to Associate, RWD Analysts
- Participate in department meetings to share knowledge and insights
- Maintain a standard of personal behavior and business ethics in line with Fortrea culture
Business Development:
- Contribute to repeat business through delivery of quality analyses and deliverables
Qualifications:
- Bachelor’s degree in statistics, mathematics, epidemiology, or another relevant field
- ≥3 years of health research data analysis experience
- Proficiency in relevant programming language that meets current client demand (e.g., SAS, R, Python)
- Proficiency in SAS macro language
- Working knowledge of Microsoft Word, PowerPoint, and Excel
- Ability to solve problems independently
- Ability to follow defined processes
- Strong attention to detail
- Strong oral and written communication
- Team player mentality
Preferred Qualifications:
- Bachelor’s degree or higher with a strong focus in statistics
- Experience conducting analyses of observational study data
- Proficiency in CDISC standards (e.g., writing SDTM and ADaM specifications)
- Experience applying CDISC standards to observational study data
- Analytic experience with existing secondary data sources (e.g., claims, hospital administration, electronic health records, registries)
- Ability to challenge conventional thinking to develop solutions