Data Warehouse Analyst - Hybrid Tallahassee, FL

2.1 Primary Job Duties and Tasks

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 through data insights.

c. Design and maintain dashboards and reports using tools like Tableau or AI-Generated web-based dashboards. Present findings to stakeholders in a clear, actionable format.

d. Work with internal teams, external partners, and leadership to define data needs and deliver solutions. Present findings to stakeholders in a clear, actionable format.

e. Ensure all work aligns with Agency’s regulations, including HIPAA and state data governance standards. Document methodologies, data sources, and assumptions for transparency and reproducibility.

f. Support special projects, audits, and federal reporting initiatives as needed.

g. Assist in the development of technical documentation for recurring reports, data pipelines, 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 risk stratification models.

j. Perform other duties as required.

2.2 Specific Knowledge, Skills, and Abilities (KSAs)

Minimum Qualifications:

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.

g. Strong understanding of Fraud Analysis methodologies.

Preferred Qualifications:

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.

2.3 General Knowledge, Skills and Abilities (KSAs)

The submitted candidate(s) must be able to apply common knowledge, skills, and abilities in the following areas:

· Communication: The ability to clearly convey information, in both written and verbal formats, to individuals or groups in a wide variety of settings (i.e.; project team meetings, management presentations, etc.). Must have the ability to effectively listen and process information provided by others.

· Customer Service: Works well with peers, clients, and customers (i.e.; business office, public, or other agencies). Able to assess the needs of the customer, provide information or assistance to satisfy expectations, or resolve a problem. Always courteous and professional.

· Decision Making: Makes sound, well-informed, and objective decisions. Asks questions and escalates to the manager if unsure on how to proceed.

· Flexibility: Is open to change, new processes (or process improvement), and new information. Has the ability to adapt in response to new information, changing conditions, or unexpected obstacles. Ability to receive and give constructive criticism and maintain effective work relationships with others.

· Interpersonal: Shows friendliness, courtesy, understanding, and politeness to others.

· Leadership: Motivates, encourages, and challenges others. Ability to adapt to leadership styles in a variety of situations.

· Problem-Solving: Able to identify, evaluate, and use sound judgment to generate and evaluate alternative actions, and make recommendations accordingly.

· Team Building: Encourages, inspires, and guides others toward accomplishing the common goal.

2.4 Education and Certifications

Education: Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, or a related field.

Certifications: Not Required