Database Analyst (C. Advanced)

a.Analyze Medicaid claims, eligibility, provider, and encounter data to identify trends,anomalies, and opportunities for improvement. b.Support program evaluation, policy analysis, and operational decision-making throughdata insights. c.Design and maintain dashboards and reports using tools like Tableau or AI-Generatedweb-based dashboards. Present findings to stakeholders in a clear, actionable format. d.Work with internal teams, external partners, and leadership to define data needs anddeliver solutions. Present findings to stakeholders in a clear, actionable format. e.Ensure all work aligns with Agency’s regulations, including HIPAA and state datagovernance standards. Document methodologies, data sources, and assumptions fortransparency and reproducibility. f.Support special projects, audits, and federal reporting initiatives as needed. g.Assist in the development of technical documentation for recurring reports, datapipelines, and reporting logic to ensure consistency and knowledge transfer. h.Develop and validate data extracts for federal and state reporting requirements,including CMS submissions and performance metrics. i.Apply machine learning methods where appropriate to improve forecasting and riskstratification models. j.Perform other duties as required.

a. Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, or a related field. b. 5+ years of experience in data analysis, preferably in healthcare or Medicaid. c. Strong proficiency in SQL/SAS, with working knowledge of Python for data manipulation, analysis, and automation tasks. d. 3 years of experience with data visualization tools such as Tableau, or similar platforms for building dashboards and reports. e. Strong understanding of healthcare data, especially Medicaid or claims-based data. f. Excellent communication skills and ability to present complex data to non-technical audiences., a. Experience working with state or federal healthcare programs. b. Knowledge of Medicaid managed care, long-term services and supports (LTSS), or waiver programs. c. Familiarity with cloud-based data platforms (e.g., Azure, AWS). d. Experience with machine learning or advanced statistical modeling.