Heading

United States

Internship

Remote

Intern

Precision AQ is a company focused on real-world evidence in healthcare. They are seeking a HEOR Intern to assist with internal process improvements and support ongoing research projects related to public health and life sciences.

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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

Qualification

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
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