Manager

  • location: New York, NY
  • type: Permanent
  • salary: $100,000 - $140,000 per year
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job description

Manager

Permanent position: My client is a leading global pharma-focused consultancy and market research firm. We have 3 openings from entry level PhD with Health Outcomes Publications experience and 4-5 years of related University research work, or someone with an MS in Epi, Psych, MPH, or econ and 3-4+ years of HE or RWE consulting experience. A manager description is below, but we are open to someone slightly higher, or lower who meets all of most of the qualifications below. Location is flexible with a remote option for senior candidates and offices located in NYC, North Philly, SF/San Mateo, and St. Louis.

Responsibilities for the Manager
  • Be the Principal Investigator, lead the design and execution of health outcomes studies including writing research proposals, designing questionnaires, overseeing statistical analysis plan (SAP) development, overseeing data analysis, providing analytical interpretation, writing reports, and writing abstracts, posters, and manuscripts
  • Successfully lead engagements to ensure client satisfaction and ensure deliverables are sent on time and are of rigorous scientific quality
  • Attend and present at professional conferences
  • Mentor junior research staff (preferred at manager level or higher)
  • Support business development activities to identify opportunities, set appropriate pricing, and submit proposals
Requirements for the Manager

  • Minimum a MPH or Master's with 3+ years of industry experience or PhD with 5 years of independent/University research experience - advanced degree in epidemiology, economics, psychology, public health, or related discipline
  • Must have experience in survey design and quantitative methods such as patient-reported outcome measurement development (Classic Test Theory and IRT knowledge) and/or patient preference studies (trade-off methods and DCE)
  • Knowledge of and experience working with statistics including regression techniques (OLS, logistic regression, generalized linear models), mixed models (e.g., survival and longitudinal analysis), non-parametric approaches, and data reduction techniques (e.g., factor analysis, SEM)
  • Must have a strong publication history with multiple peer-reviewed manuscripts
  • Advanced ability to analyze data using SAS, SPSS, Stata, Mplus, and/or R
Benefits

    Equal Opportunity Employer: Race, Color, Religion, Sex, Sexual Orientation, Gender Identity, National Origin, Age, Genetic Information, Disability, Protected Veteran Status, or any other legally protected group status.

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