HEOR Intern, Real-World Evidence at Precision AQ in Remote

Summary: Precision AQ is a company focused on healthcare and real-world evidence. The HEOR Intern will assist in streamlining internal processes and support ongoing research projects related to public health and life sciences. Responsibilities: - 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 Required Qualifications: - 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 - 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 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 Qualifications: - 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 Required Skills: Epidemiology, Biostatistics, Bioinformatics, Economics, Data Science, Life Sciences, Healthcare Research, Pharmaceutical Research, Public Health, Health Services Research, Health Policy, Statistical Programming - R, Statistical Programming - SQL, Statistical Programming - SAS, Observational Study Designs, Measures of Association, Bias, Confounding, Microsoft Office