Location: Plantation, FL
Participate in design reviews and provide input to the design recommendations; provide input to information/data flow, understand, and comply with Project Life Cycle Methodology in all planning steps.
Design and facilitate the implementation of technical best practices for data movement, data quality, data cleansing, and other ETL-related activities.
Debugging Data and performing data validation using SQL queries to support different reports such as OPPE (Ongoing Professional Provider Evaluation), Provider bonus reporting.
Identifying, analyzing, and interpreting billing data sets coming from different hospitals and billing systems to find patterns and trends.
Converting billing data into usable information that further helps to create reports to submit to CMS (Center of Medicare and Medicaid) and NRDR (National Radiology Data Registry) for e.g. MIPS (Merit Based Incentive Payment System) and OPPE.
Developing and implementing data analysis, data collection systems and other strategies that optimize statistical efficiency and quality of the relational database.
Work with Business Analysts, Developers, Database Administrators, ¬Data Architects to ensure business requirements are being met with the solutions being developed.
Creating functional requirement document to present the stakeholder’s requirements in a format which would enables the data architect to build multidimensional cube (OLAP) with the required KPIs and measures.
Creating various ad-hoc reports requested by stakeholders across all line of business, to provide insights of the billing information which is accumulated in the enterprise data warehouse.
Supporting the data warehouse in identifying and revising reporting requirements.
Preparing reports for executive leadership that effectively communicate trends, patterns, and predictions using relevant data.
Designing and maintaining data systems and databases; this includes fixing coding errors and other data-related problems.Creating an Analytical model to identify the Post-op complications using various algorithms and showing the results using Power BI across different facilities, which further compared to the benchmark.
Gather business and technical requirements to identify detailed data requirements, data definitions, data lineage and relevant business rules.
Creating an automated Compensation Model for Providers based on the compensation business requirements which allows providers to get paid.
Developing and implementing data analyses, data collection systems and other strategies that optimize statistical efficiency and quality.