Data Warehouse Jobs in Florida (NOW HIRING)

Primary Job Duties and Tasks

 Analyze Medicaid claims, eligibility, provider, and
encounter data to identify trends, anomalies, and
opportunities for improvement.
 Support program evaluation, policy analysis, and
operational decision-making through data insights.
 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.
 Work with internal teams, external partners, and
leadership to define data needs and deliver
solutions. Present findings to stakeholders in a
clear, actionable format.
 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.
 Support special projects, audits, and federal
reporting initiatives as needed.
 Assist in the development of technical
documentation for recurring reports, data
pipelines, and reporting logic to ensure
consistency and knowledge transfer.
 Develop and validate data extracts for federal and
state reporting requirements, including CMS
submissions and performance metrics.
 Apply machine learning methods where
appropriate to improve forecasting and risk
stratification models.

 Perform other duties as required.
Specific Knowledge, Skills, and Abilities (KSAs)
 Minimum Qualifications
 Bachelor’s or Master’s degree in Data Science,
Statistics, Computer Science, or a related field.
 5+ years of experience in data analysis, preferably
in healthcare or Medicaid.
 Strong proficiency in SQL/SAS, with working
knowledge of Python for data manipulation,
analysis, and automation tasks.
 3 years of experience with data visualization tools
such as Tableau, or similar platforms for building
dashboards and reports.
 Strong understanding of healthcare data,
especially Medicaid or claims-based data.
 Excellent communication skills and ability to
present complex data to non-technical audiences.
 Strong understanding of Fraud Analysis
methodologies.
 Preferred Qualifications:
 Experience working with state or federal
healthcare programs.
 Knowledge of Medicaid managed care, long-term
services and supports (LTSS), or waiver programs.
 Familiarity with cloud-based data platforms (e.g.,
Azure, AWS).
 Experience with machine learning or advanced
statistical modeling.
General Knowledge, Skills and Abilities (KSAs)
 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.
Education and Certifications Education
 Bachelor’s or Master’s degree in Data Science,
Statistics, Computer Science, or a related field.