Oncology RWD Programmer

Oncology RWD Programmer

OVERALL RESPONSIBILITIES:

The Oncology RWD Programmer will conduct statistical analyses of real-world data to address critical questions on the safety and benefit-risk of products within the Oncology Therapeutic Area. Additional activities include the development and generation of analysis datasets, tables, listings, and graphs from assigned clinical and real-world data sources. This individual will perform with minimal supervision under the direction of Oncology therapeutic area epidemiologists.

POSITION DUTIES & RESPONSIBILITIES:

• Conduct analyses and develop specifications for descriptive and comparative safety studies utilizing real world data within the Oncology therapeutic area
• Utilize programming standards to develop efficient and accurate programs
• Collaborate with epidemiologists to develop code lists for disease areas
• Support programming deliverables for re-analysis of clinical trial data and support for any custom real world data reports
• Provide quality programming deliverables and conduct QC on analyses as needed

Functional and Technical Competencies:

• Competencies in SAS, R or SQL required
• Demonstrated ability to work in teams is required
• Master’s degree (e.g. MA, MSc, MPH) in Biostatistics, Epidemiology, Health Services Research, or related discipline, such as Outcomes Research from an accredited institution, with a minimum of three (3) years of relevant, post-graduation experience OR a Bachelor’s degree in Statistics, Computer Science or related discipline, with at least five (5) years of experience analyzing observational data is required
• Experience in the analysis of real-world data sources is required
• Experience with US Oncology specific real-world data sources is preferred
• Knowledge and experience in clinical and observational research study design, execution and communication is preferred
• Writing Statistical Analysis Plans (SAP) for descriptive and comparative studies in real-world data, including claims and EHR is preferred
• Understanding of the analysis of real-world data for regulatory submissions is preferred