HEOR Intern, Real-World Evidence

Essential duties include but are not limited to

Help streamline internal processes – work directly with the Precision leadership to improve processes and efficiency; investigate optimal research techniques and implementation strategies; update existing tools and documentation to increase adherence to best practices; support development and refinement of interactive tools that use existing real-world evidence analyses.

Support ongoing research projects – assist with literature reviews on diverse healthcare topics; help with real-world evidence studies including protocol development, data programming, and results; develop interactive summaries of real-world evidence analyses; help interpret and communicate quantitative and qualitative findings to internal and external audiences; contribute to reports, results tables, presentations or peer-reviewed manuscripts; participate in client-facing activities; provide administrative project support.

Qualifications

Required

• Enrolled in a public health (epidemiology, biostatistics, bioinformatics), economics, data science, life sciences, or healthcare related undergraduate, or preferably, graduate program at an academic institution at the time of recruitment.

Other required

• Proven interest in public health, life sciences, or pharmaceutical research and analytics
• Research experience in epidemiology, public health, health services research, health policy, economics or related fields
• Foundational knowledge of epidemiologic concepts such as observational study designs, measures of association, and common sources sources of bias and confounding
• Familiarity / competency with statistical programming tool such as R, SQL, SAS or similar platform
• Ability to work effectively both individually and as part of a team
• Detail oriented with exceptional interpersonal and time management skills
• Keen interest in learning and sharing knowledge
• Strong academic record
• Proficiency with Microsoft Office

Preferred

• Enrolled in life sciences related advanced degree program
• Strong understanding of the scientific method; formal training in quantitative methodologies
• Familiarity with interactive data visualization tools such as R Shiny, Power BI, Tableau, or equivalent platforms
• Familiarity with working in virtual AWS environment, Git, and Github

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Precision Medicine Group is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, age, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status or other characteristics protected by law.

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