Data Analyst

  • Kristian N. Business Analysis, Microsoft SQL Server, Full Stack, Python

Business Analysis, Microsoft SQL Server, Full Stack, Python

13/11/2022 - ΕΝΕΡΓΟ

Ελλάδα / Αττική / Αθήνα, 18544

Master’s

Πλήρης απασχόληση

Έτη Εμπειρίας: 1-3

/ Ναι / Όχι

Εμφάνιση Τηλεφώνου

  • Project: Demonstrating Utilization Management Value: An In-depth Analysis of Outcomes after Cardiology Procedures Denials • An analysis based on combined pre-authorization and claims data. • Classifying patient on four event of our interest and interpreting result through visualization. • Build appropriate regression model for the number of services. • In addition to the clinical outcomes, a financial overview of the events is performed. • Creating KPI dashboard
  • MSc in Applied Statistics, New Jersey Institute of Technology, Newark, New Jersey, USA (Expected) 2021-2022 Current GPA: 4.00 • Highlander Retention Scholarship: Scholarship received based on academic standings Spring 2022 • Masters’ Projects: – Confidence intervals for Kaplan-Meier estimator using non-parametric Maximum Likelihood Ratio Test, Supervi- sor: Professor Sundars Subramanian – Predictive Accuracy in Cox models using ROC Curves, Supervisor: Professor Sundars Subramanian – Indicating Curvature in 2 k Factorial Design, Supervisor: Professor Sunil Dhar – D-Optimal Design “Minimizing The Variance of the Regression Coefficients”, Supervisor: Professor Sunil Dhar – Estimating Interblock and Intrablock Treatment Effects for Balanced Incomplete Block Design, Supervisor: Pro- fessor Sunil Dhar – Proportional Hazard Models for acute myocardial infarction, Supervisor: Professor Ji Me Loh – Explanatory Data Analysis and Modeling Cancer data, Supervisor: Professor Ji Me Loh BSc in Applied Mathematics, National Technical University of Athens, Greece 2015-2020 Steam-Courses: Statistics, Applied Analysis • Thesis title: ‘Cox’s Semi-Parametric Proportional Hazard Model and Shrinkage Estimation Methods, using R’. Su- pervisor: Professor Chrysseis Caroni • Project title: ‘Parametric and Semi-Parametric Regression Models for Patients Survival, using R’. Supervisor: Pro- fessor Chrysseis Caroni.
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