job title: Real world evidence analyst 2

Roles and Responsibilities

• Provide programming support for the analysis of real-world data from diverse sources including medical and pharmacy claims data, hospital data, electronic medical record data, and prospective observational study data.

  • Help in contributing to the development of programming specifications based on analysis requirements and source data.

  • Develop and validate analysis datasets from various file formats and sources, both internal and external.

  • Assist in the development and validation of graphs and tables for exploratory investigations, adapting to changing analysis requirements.

  • Ensure excellence in the programming of analysis-ready datasets, tables, listings, and figures, including associated validation work.

  • Support the creation and maintenance of documentation for assigned deliverables.

  • Assist in communicating accurate and timely status updates to project leads and team members.

  • Participate in department meetings to share knowledge and insights.

  • Assist in identifying opportunities to enhance productivity, quality, and efficiency in programming processes.

  • And all other duties as needed or assigned.

  Experience (Minimum Required):

  
  • Typically, 1-3 years of RWE analysis experience in the CRO or Pharmaceutical Industry, or an equivalent combination of education and experience to successfully perform the key responsibilities of the Job.

  • Experience in handling data from Electronic Health Records (EHR)/Claims databases (Optum, Marketscan, Flatiron etc.) is required.

  • Proficiency in SAS and SQL programming.

  
  Preferred Qualifications Include:
  • Experience in programming languages such as R and Python.
  • Experience with handling big data, non-standard/new data, and complex data.
  • Expertise in creating various types of graphs for data presentation.
  • Strong analytical mindset and logical thinking capability.
  • Positive attitude and willingness to learn and contribute to a team setting and communicate effectively within the team environment.
  • Willingness to gain experience in working with real-world data from health insurance claims, retrospective analyses, manual chart reviews, prospective observational studies, and pragmatic clinical trials.
  • Good understanding of advanced statistical and econometric methods in theory and practice.