- Knowledge and skills: Working knowledge about complex structure of Medicare data; Medicare data programming skills to perform data management, cohort creation, and statistical analysis for pharmacoepidemiology or health services research; and ability to organize analytical tasks and documentation files in a rigorous and reproducible fashion
- Responsibility: Willingness to share ownership and responsibilities of the ongoing projects with PI and other investigators
- Leadership: Ability to identify and address areas of inefficiencies in the research process and train other team members (e.g., research assistants, research associates, data scientists, and researchers) to maximize the team performance and productivity
- Project management: Ability to work on multiple projects, prioritize tasks, develop workflow, and meet study deadlines
- Communication: Ability to speak and write in English to communicate research procedures and results
- Teamwork and collaboration: Works effectively within a team, group and across the organization and accomplishes tasks and desired results while behaving constructively as opposed to separately and competitively
- Perform data management (e.g., convert raw datasets to common data model datasets, standardize variable definitions) of Medicare data, and create and maintain clear and easy to follow documentation of programs, analytic datasets, and other project-specific file to facilitate replication, reproducibility and archiving of projects.
- Create an analytical cohort according to the analysis protocol prepared by the investigators (a typical cohort includes some index event [e.g., drug prescribing or surgical procedure] and measurement of baseline covariates and outcome variables [e.g., time to event, count of health care utilization, and cost]).
- Perform statistical analysis under the instructions of investigators and biostatistician (e.g., propensity score analysis and regression models for continuous, binary, count, and time-to-event variables).
- Work to improve the efficiency of the data analysis process by identifying and addressing inefficiencies, developing a workflow, and standardizing repetitive procedures. Develop SAS programs that are flexible, reusable, scalable, computationally efficient, and maintainable. Establish protocols for quality control to ensure accuracy of programming.
- Train, supervise, and support the development of other team members (e.g., research assistants, research associates, data scientists, and researchers) in using Medicare data and programming. Provide advice and consultation to the investigators in developing analysis protocols.
- Oversee the progress of multiple data analysis projects under competing deadlines, create timelines, prioritize tasks, communicate changes to the timelines with researchers, and meet the study deadlines
- Assist the investigators in scientific presentation, manuscript writing, and grant writing by providing sample size count and preparing tables and figures from the analysis
- The above covers the most significant responsibilities of the position. It does not, however, exclude other duties, which would be in conformity with the level of the position. Completes special projects as assigned .
- Must have professional experience of 5 or more years in Medicare data programming for pharmacoepidemiology or health services research. Masters degree or doctoral degree in related field (e.g., public health, epidemiology, statistics, quantitative social sciences, or economics) preferred.
- Must be proficient in SAS. Experience with Stata, Excel, R, and Python a plus. Familiarity with SQL is strongly preferred.
- Must have strong experience with medical coding systems (e.g., NDC, ICD-10, HCPCS, CPT) and an understanding of epidemiologic principles and basic medical terminology.
- Must have ability to work on multiple projects, adapt to project demands, prioritize tasks, develop workflow, and meet study deadlines.
- Must have ability to work with minimal supervision, be self-motivated, and work independently and as a part of a team.
- Must have good problem-solving skills, provide leadership to the team when required, oversee the work of research staff, and directly manage research staff
- Must exhibit respect for participant confidentiality (including compliance to HIPAA Protected Health Information regulations), excellent communication skills, careful attention to details, good organizational skills, and ability to follow directions.
- Must be professional, proactive, collaborative, conscientious and results-oriented individual. Must have an optimistic and positive demeanor, excellent oral and written communication skills, good intuition and able to adapt to changing priorities and display good, sound judgment.
- Must be motivated to learn and flexible to change.
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