Blu Omega · 1 day ago
Senior Health Analytics Consultant
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Responsibilities
Independently perform a broad range of quantitative analysis to inform the design, implementation, and evaluation of Medicare and Medicaid payment models
Develop strategic working relationships with clients
Design payment calculations, conduct financial and trend analysis, calculate quality metrics, and perform fast-paced ad-hoc analysis to quickly address client needs
Efficiently query large databases of healthcare claims and eligibility data
Apply machine learning, econometrics/statistics, predictive modeling, return-on-investment analysis, simulation, and data visualization methods to support the development of health policy
Mentor other staff to develop their technical and analytical problem-solving skills
Write detailed specifications and documentation of data processing and analytical steps
Write effective and efficient code both independently and under the guidance of project managers using best practice quality control procedures
Maintain a consistently high degree of accuracy and attention to detail in all tasks
Work effectively and cooperatively as a member of a project team
Qualification
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Required
Master’s degree or higher in Statistics, Economics, Public Health, Public Policy, or related field
Experience leading statistical analysis to inform health policy
Familiarity with Medicare and Medicaid payment methodologies
Experience working with healthcare claims and enrollment data
Extensive knowledge of healthcare data/payment concepts (e.g., claims data structure/contents, claim types)
6+ years of experience using SAS (including macro processing and Proc SQL), R, Python, or SQL in a research, consulting, or business environment
Experience working with and advising clients
Excellent written and oral communication skills, including the ability to clearly communicate analyses and findings to clients
Preferred
Ph.D. in Statistics, Economics, Public Health, Public Policy, or related field
Experience with databases having complex structures and relationships, such as the Integrated Data Repository, Chronic Conditions Warehouse, or similar data environment
Proficient in managing and analyzing large datasets using SAS grid and other parallel processing techniques
Experience with other software such as Excel (e.g., pivot tables, VBA) or Tableau
SAS certification