RWE (Real World Evidence) SAS Programmer, CDISC/SDTM specs

Job Overview:

The RWE SAS Programmer, CDISC/SDTM specs position is responsible for supporting our 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 (e.g., claims, hospital administration, electronic health records, registries). The Senior Associate, RWD Analyst follows analytic plans for data presentation under the guidance of our RWE biostatisticians and epidemiologists.

Summary of Responsibilities:

Client Delivery

• Provide programming for the analysis of RWD from diverse sources including observational studies and existing secondary data sources (e.g., claims, hospital administration, electronic health records, registries)
• 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
• And all other duties as needed or assigned

Qualifications (Minimum Required):

• Bachelor’s degree in statistics, mathematics, epidemiology, or another relevant field
• Fortrea may consider relevant and equivalent experience and successful project outcomes in lieu of educational requirements
• 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

Experience (Minimum Required):

• ≥3 years of health research data analysis experience

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

Physical Demands / Work Environment:

• Home-based environment
• Varied hours may be required
• On occasion, must be able to work in the evenings and on weekends to meet project deadlines
• Ability to work in an upright and/or stationary position for 6-8 hours per day
• Repetitive hand movement of both hands with the ability to make fast, simple, repeated movements of the fingers, hands, and wrists to operate lab equipment
• Occasional crouching, stooping, with frequent bending and twisting of upper body and neck
• Ability to access and use a variety of computer software developed both in-house and off-the-shelf
• Light to moderate lifting and carrying, or moving of objects, including luggage and laptop computer with a maximum lift of 15-20 lbs
• Regular and consistent attendance

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