RWE Analyst

Job Title : RWE Analyst Location : Remote Contract Duration: longterm Only W2 or 1099 Day-to-Day Job Duties • Engage with life sciences and healthcare clients to understand business, research, and analytics requirements. • Analyze and interpret Real-World Data (RWD) from healthcare claims, EHR, and other healthcare data sources to generate actionable insights. • Design, develop, and validate analytical solutions using SAS, R, SQL, and Python. • Collaborate with cross-functional teams including researchers, statisticians, data engineers, and client stakeholders. • Support data modeling, statistical analysis, and reporting activities for healthcare and life sciences projects. • Apply SDLC best practices, version control, and code management standards in project delivery. • Explore and implement AI-enabled solutions, automation opportunities, and productivity accelerators to improve project outcomes. • Create project documentation, technical specifications, methodologies, and client presentations. • Participate in client meetings, workshops, solution reviews, and knowledge-sharing sessions. • Mentor junior team members and contribute to consulting practice development initiatives. Basic Qualifications • Bachelor's degree in Computer Science, Statistics, Mathematics, Life Sciences, Data Science, or related discipline. • 6+ years of experience in healthcare analytics, statistical programming, data engineering, consulting, or software development within life sciences, healthcare, or research environments. • Minimum 5+ years of hands-on experience with SAS and/or R for statistical programming and analysis. • Minimum 4+ years of experience with SQL for data extraction, transformation, and analysis. • Minimum 3+ years of experience with Python for analytics, automation, or data engineering activities. • Strong understanding of Real-World Evidence (RWE), healthcare claims, and Electronic Health Record (EHR) data. • Experience working in global delivery or consulting environments with client-facing responsibilities. • Strong analytical, problem-solving, communication, and stakeholder management skills. Degree: Bachelor's degree in Computer Science, Statistics, Mathematics, Life Sciences, Data Science, or a related field.