Ann-Marie Akiwumi

Ann-Marie Akiwumi is a principal data scientist in the Health program at AIR. She has over 13 years of experience conducting focused analytic studies and advanced analytics using a variety of large disparate data including Medicare and Medicaid administrative, Marketplace, health equity, and social determinants of health (SDOH) data. As part of the Health leadership team, Akiwumi serves as data analytics lead for the division’s data analytic portfolio and manages its large and diverse teams of SAS programmers, software developers and data scientists. She brings a strong history of creating, implementing, and standardizing efficient operations of data analytic contracts.

Akiwumi’s utilizes her quantitative expertise in data analytics and data flow and systems, and her qualitative experience in stakeholder engagement, systems thinking, and conceptual model development in the projects she supports. As Data Analytics Lead for the NIH-funded Rapid Acceleration of Diagnostics, Underserved Populations (RADx-UP) Coordination and Data Collection Center project, she leads the AIR team with data linkage, building automated tools for generating summary reports, extract, transform and load data, measure development, and data aggregation. She also facilitates and engages with researchers, community and governmental leaders to conceptualize their experiences, ideas, and recommendations to overcome disparities in COVID-19 testing. As key data analytics lead on the Marketplace Operations Support project for Centers for Medicare & Medicaid Services’ Center for Consumer Information and Insurance Oversight (CCIIO), she provides data analytic and technical assistance oversight including web scraping, data matching and process automation. Akiwumi leads the development and maintenance of the SDOH Action Tool, a data visualization tool that highlights which evidence based SDOH factors are affecting population health at the local level.

Previously, Akiwumi led a team of modelers to develop and implement predictive, rule-based, and anomaly studies in SAS and SPSS for program integrity end users utilizing Medicare, Medicaid, and Medi-Medi claims data. She also led the querying of Medicaid Data warehouses for New Jersey, New York, and Pennsylvania and conducted focused analyses on transportation services, long-term care, community-based waivers, children's school services, and provider and beneficiary enrollment. She is Project Management Professional (PMP) certified.