Transforming raw data into actionable insights that drive the efficient operation of ambulatory clinics, identify trends, optimize performance, and support data-driven decision-making to enhance financial viability and operational efficiency.
Requirements
- Minimum of 5 years of experience with Python or R for data analysis, modeling, and machine learning applications.
- Proven expertise in data modeling, information design, and data integration.
- Advanced knowledge of data management systems, practices, and standards.
- Experience with complex data quality, governance issues, and data conversion.
- Ability to abstract and represent information flows in systems through effective modeling.
- Experience with Databricks, including managing and processing large datasets in a distributed environment.
- Experience with Azure DevOps, including managing workflows, version control, and collaborative project management.
Responsibilities
- Develop, refine, and maintain complex data models that support ambulatory operations, ensuring data accuracy and consistency.
- Apply statistical analysis and machine learning techniques to analyze large datasets, identify trends, and generate predictive insights.
- Design and implement predictive models to forecast key performance indicators, patient outcomes, and ambulatory operational efficiencies.
- Create and validate algorithms for data mining, cleansing, and transformation to enhance data usability
- Lead or participate in projects focused on enhancing data infrastructure, analytical capabilities, and reporting frameworks.
- Explore and implement innovative data science techniques and tools to address complex challenges in ambulatory operations.
- Develop and manage ETL (Extract, Transform, Load) processes to curate data from various sources into structured formats suitable for analysis.
Other
- Minimum of 3+ years of experience in a healthcare-related organization, with a strong understanding of healthcare data and operations
- Strong analytical and problem-solving skills with attention to detail.
- Excellent communication and interpersonal skills, with a demonstrated ability to work collaboratively across diverse teams.
- Present findings and recommendations to leadership and other stakeholders in a clear, concise, and actionable manner.
- Provide guidance and mentorship to analysts within the team
