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Real World Evidence (RWE) Analyst
Job Description
• Support development of and provide critical appraisal of study protocols for research projects using RWD (e.g., medical claims, EHR, and observational registry databases)
• Partner closely with internal and external stakeholders, including the Biostatistics and Programming team, to develop statistical analysis plans using descriptive and complex study designs
• Lead or support generation of code lists and identification of claims- or other RWD-based algorithms applicable to RWD research, by working collaboratively with internal/external researchers and/or via literature review
• Lead or support data analyses/QC using claims, EHR, and/or registry databases in close collaboration with internal and external stakeholders
• Conduct thorough data reviews for primary/secondary data collected to ensure quality and reliability
• Communicate the study results with a broader audience internally and externally
• Effectively manage internal and external stakeholder expectations regarding strategic objectives and execution of research
• Support cross-functional initiatives to develop and refine internal procedures, workflows, and best practices
Basic Qualifications
• Master’s degree in Epidemiology, Biostatistics, Statistics or related discipline from an accredited institution and 4+ years of experience working with a broad range of RWD, in academia, at a contract research organization, or in the biopharmaceutical industry
Preferred Qualifications:
• Doctoral level training in Epidemiology, Biostatistics, Statistics or related discipline from an accredited institution
• 4+ years of oncology research experience highly preferred
• Prior experience of using RWD in regulatory applications, post-marketing studies, and pharmacovigilance
• Prior experience in projects involving Flatiron EHR and/or chart review data from clinical sites
• In-depth knowledge of claims-based RWD (e.g., Optum, HealthVerity) and prior experience of using claims-based RWD in oncology research
• In-depth knowledge of advanced statistical methods to support complex study designs
• Proficiency in statistical analysis programming languages commonly used in life sciences (e.g., SAS, R)
• Excellent interpersonal communication and study management skills
• Excellent verbal, written and presentation skills, including the ability to effectively communicate study results in a clear, non-technical manner to internal cross-functional teams, using language that resonates with the teams, while maintaining the integrity of key findings
• Ability to work effectively in a constantly changing, diverse, and matrix environment
Pay ranges between $70-77/hr based on experience
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Planet Pharma is an equal opportunity employer. It is our practice not to discriminate against any employee or applicant based on any criteria, condition or basis protected by laws or regulations in the locations where we do business. All qualified applicants are encouraged to apply. We celebrate diversity and are committed to providing an environment of mutual respect. We believe that diversity, equity and inclusion enable us to better meet our mission and values while serving our clients across the globe. If you have a disability or handicap and would like us to accommodate you in any reasonable way, please inform your recruiter, or contact us, so that we can discuss the appropriate alternatives available.
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