PAI is seeking experienced HEOR modelers to join its growing team. The HEOR Modelers will work with PAI consultants and principals to deliver research and consulting projects of the highest quality to our clients. In this role, the HEOR Modeler will have responsibility for design, development, and estimation of economic models to quantify the clinical and/or economic impacts of novel biopharmaceuticals. It is expected that the roles and responsibilities of the Modeler will grow over time.
Responsibilities
The main responsibilities of the HEOR Modeler will include:
Develop complex HEOR models in Microsoft Excel including cost-effectiveness and budgetary impact models
Conduct statistical analyses of clinical trial data and other data using R (preferable) and/or SAS
Collect and synthesize clinical, epidemiologic, and economic evidence using systematic and nonsystematic reviews of the literature and other sources
Conduct meta-analyses and network meta-analyses (NMAs) of aggregate data from controlled clinical trials using Bayesian and other methods
Prepare model specifications, study protocols, and study reports
Communicate study methods and results to clients
Manage and mentor more junior staff
Collaborate with other staff to develop new analytic tools and service offerings
Requirements
Minimum requirement for the position include:
Two or more years of experience in biopharmaceutical industry, HEOR consulting, or academia developing and estimating cost-effectiveness and/or budgetary impact models in Excel
Expert level of proficiency with Excel including VBA, array formulas, and dynamic named ranges
Experience in data analysis using R (preferable) or SAS
Exceptional analytical and problem-solving skills
Excellent English-language verbal and written communication skills
Ability to work independently on multiple projects in an intellectually challenging environment
Desire to learn, grow, and advance within the organization
The ideal candidate will also have
Master’s degree (or higher) in related discipline (e.g., economics, mathematics, public health, pharmacy)
High level of proficiency with statistical analysis software such as R (preferable) or SAS
Experience conducting survival analysis and longitudinal data analysis
Experience with methods to adjust for time-dependent confounding or censoring including structural models for causal inference
Experience in development and estimation of models for submissions to reimbursement authorities such as the National Institute for Health and Care Excellence (NICE)
Position Type
Full time salaried
Location
Brookline, Massachusetts
Candidates without the requisite experience developing cost-effectiveness and/or budgetary impact models will not be considered and need not apply.
