Health Economics Associate- Advanced Analytics

Job description

When our values align, there's no limit to what we can achieve.   At Parexel, we all share the same goal - to improve the world's health. From clinical trials to regulatory, consulting, and market access, every clinical development solution we provide is underpinned by something special - a deep conviction in what we do. Each of us, no matter what we do at Parexel, contributes to the development of a therapy that ultimately will benefit a patient. We take our work personally, we do it with empathy and we're committed to making a difference. Key Accountabilities: Project Execution • Acting as support biostatistician or statistical programmer to interact with the study team and the sponsor • Support in drafting statistical sections of protocols, performing sample size and power calculation for studies. • Supporting in reviewing data management plans, data specifications, and other related study documents • Supporting in developing statistical analysis plans • Contributing to the preparation of specifications for analysis datasets • Supporting in developing statistical programs to generate listings, tables and figures as outlined by a statistical analysis plan • Performing QC of TLFs and other analysis datasets • Providing statistical input to Clinical Study Reports • To help ensure quality standards are adhered to on all projects and new methodologies and techniques are adequately assessed and implemented. • To help foster thought leadership opportunities. Skills: • Ability to manage priorities to meet multiple and sometimes competing deadlines. • Excellent scientific, business writing, and presentation skills with attention to detail. • Exceptional communication skills, especially in the relaying of technical information and project concepts. • Competent in written and spoken English • SAS, R, SQL, and/or Python Knowledge and Experience: • 2-4 yrs of experience with familiarity in healthcare consulting or pharmaceutical organizations. • Strong basis in fundamental statistical concepts and methods and familiarity with techniques such as development of predictive equations, survival analysis (including parametric methods), longitudinal data analysis, meta-analysis, mixed treatment comparison, and other hierarchical analysis techniques, etc. • Familiarity with machine learning techniques and Bayesian statistics is a plus. • Strong statistical programming skills with standard software. • Strong communication (spoken and written) and problem-solving skills, and an ability to learn-quickly. • Ability to communicate effectively, in non-technical terms, with project team members. • Ability to work well in a team as well as independently and be able to take leadership role with regard to methodological elements in projects. Education: • Master or higher degrees in Public Health, Health Economics, Health Policy, Statistics, Biostatics, Mathematics, or other quantitative fields.