Palm Medical Centers
Healthcare Claims Data Analyst
Coral Gables, FL - Full Time
Palm Medical Centers is seeking a highly analytical and detail-oriented Healthcare Claims Data Analyst to join our team. The ideal candidate will have extensive experience working with healthcare claims data across various medical specialties. This role is focused on identifying opportunities to enhance clinical outcomes and improve operational efficiency through data-driven insights. The candidate must be local to the Miami, Florida area and commute daily to Coral Gables headquarters.
Key Responsibilities:
Schedule:
Palm Medical Centers is an equal opportunity employer that is committed to diversity and inclusion in the workplace. We prohibit discrimination and harassment of any kind based on race, color, sex, religion, sexual orientation, national origin, disability, genetic information, pregnancy, or any other protected characteristic as outlined by federal, state, or local laws.
This policy applies to all employment practices within our organization, including hiring, recruiting, promotion, termination, layoff, recall, leave of absence, compensation, benefits, training, and apprenticeship. Palm Medical Centers makes hiring decisions based solely on qualifications, merit, and business needs at the time.
Key Responsibilities:
- Analyze healthcare claims data across multiple specialties to uncover patterns, trends, and areas for improvement.
- Identify high rates of hospitalization, emergency room utilization, and other key indicators of clinical or operational inefficiencies.
- Evaluate cost drivers and specialty-specific trends to uncover opportunities for reducing expenses and enhancing care quality.
- Collaborate with clinical, operational, and management teams to translate data insights into actionable strategies.
- Develop and maintain reports, visualizations, and dashboards to effectively communicate findings to stakeholders.
- Track and assess the impact of implemented initiatives through continuous data monitoring and evaluation.
- Remain current with healthcare policies, billing practices, and industry standards that influence claims data and analytics.
- Fluency in English (verbal and written) required.
- Experience with risk adjustment methodologies and quality reporting metrics.
- Familiarity with value-based care models and population health management.
- Be willing to receive guidance in learning new efforts and grow with the challenges presented
- Bachelor's or Master’s degree in Health Informatics, Data Science, Public Health, Statistics, or a related field.
- Proven experience in healthcare data analysis, particularly working with claims data.
- Strong knowledge of healthcare systems, billing processes, and clinical terminology.
- Proficiency in data analytics tools (e.g., SQL, Python, R, SAS) and data visualization platforms (e.g., Tableau, Power BI).
- Excellent analytical thinking, attention to detail, and problem-solving skills.
- Strong communication skills with the ability to present complex findings clearly to both technical and non-technical audiences.
- Prolonged periods sitting at a desk and working on a computer.
- Must be able to lift up to 15 pounds at times.
- Majority of work is performed in a corporate office setting, indoors.
- Minimal/No travel requirement.
Schedule:
- 8 hour shift
- Day shift
- Monday to Friday
- In-person
Palm Medical Centers is an equal opportunity employer that is committed to diversity and inclusion in the workplace. We prohibit discrimination and harassment of any kind based on race, color, sex, religion, sexual orientation, national origin, disability, genetic information, pregnancy, or any other protected characteristic as outlined by federal, state, or local laws.
This policy applies to all employment practices within our organization, including hiring, recruiting, promotion, termination, layoff, recall, leave of absence, compensation, benefits, training, and apprenticeship. Palm Medical Centers makes hiring decisions based solely on qualifications, merit, and business needs at the time.
