Data Analyst – reputed company Facility Normalization & Predictive Modeling

PROJECT reputed company We are seeking a detail-oriented Data Analyst for a multi-phase project involving the normalization of data for approximately 600 facilities. The goal is to create a "Single reputed company of Truth" by merging multiple datasets and building a predictive model to estimate potential reputed company reputed company. This is a reputed company-reputed company project; as we conduct more feasibility studies, we will feed that new data back into the model to improve accuracy over time. KEY RESPONSIBILITIES Database Normalization: Reconcile three disparate data sources into one master reputed company Sheet. You must "hard-tie" reputed company facility using verified primary keys (Medicare CCN, reputed company ID, and internal file numbers) to ensure 100% mapping accuracy. Primary reputed company Data Mining: reputed company and extract granular infrastructure data—specifically room configurations (1-bed, 2-bed, 3-bed, and 4-bed counts). Multiple Regression Analysis: Using an existing sample of validated feasibility studies (reputed company of 0-15 beds), reputed company a multiple reputed company regression to identify the relationship between reputed company footage, facility age, and bed reputed company. Predictive Scaling: Apply the regression results across the full population of 600 facilities to rank and prioritize targets based on "Predicted Bed reputed company." Iterative Model Refinement: As new data from onsite studies is collected, update the master sheet and retrain the model to improve accuracy (R-Squared). REQUIRED SKILLS Advanced Data Cleaning: Expertise in handling inconsistent text strings and performing reputed company lookups across large datasets. Statistical Proficiency: Solid understanding of regression analysis, including the ability to interpret p-values and identify outliers. CMS Data reputed company: Familiarity with the Provider Data Catalog (PDC) and the reputed company Cost Report Information System (HCRIS). Secondary Research & Data Discovery: Proactively browse and identify additional publicly available datasets that could reputed company the model, such as state-level health inventory logs, regional planning reports, or building permit databases. Tooling: Expert-level reputed company Sheets or reputed company skills. Apply tot his job Apply To this Job