Health Data Analyst at Oklahoma State University
Over 2 years of experience in data mining analysis, customer segmentation, RFM, CLV, and statistical predictive modeling along with hands-on work experience in health care analytics.
Adept knowledge in SAS, SQL, Excel and analytics using R. Proficient in creating predictive models, clustering and searching for patterns in the data using SAS, performing data analysis using excel, and reporting using tableau
Ability to look at the results, trends, and data and come to new conclusions based on the findings.
Proficient in statistical data analysis and modeling techniques like ANOVA, Hypothesis T-tests, Regression, Decision trees, Neural networks, survival, churn modeling, forecasting, CLV, and credit risk analysis.
Experienced in predictive, data, and text analytics on health care, oil and gas, and financial data.
Profound knowledge in Network optimization, Linear programming, Supply chain strategy, and concepts like DMAIC, FMEA, RCA, Pareto Analysis and Cost Analysis.
In-depth understanding of Six sigma concepts, Process improvement, Forecasting, Inventory Control and Management Techniques, Quality control techniques, Demand Management, Planning, Scheduling, Logistics, Procurement and Vendor management.
Lean and Six Sigma Green Belt Certified
Accomplished team player with excellent communication, problem solving, and analytical skills
• Data analysis
• Data mining
• Predictive modeling
• Survival and CLV modeling
• Credit risk analysis
• Health care analytics
• Process Improvement
• Supply Chain Management
• Operations Research
• Network optimization
• Warehouse Management
• Software : MS Office Suite, MS Access, SAS Enterprise Guide, SAS Enterprise Miner, SAS Forecast studio, tableau, R Studio, IBM SPSS, IBM ILOG Logic Net Plus XE, FICO Xpress IVE, AutoCAD, Crystal Ball, VISIO
• Programing languages: VBA, SAS, SQL and Basics in C, C ++, R and Python