Results-oriented senior Data Architect/Engineer with proven expertise in unifying data sources and enhancing reporting efficiency. Skilled in data modeling and cloud computing, deep statistical analysis, end to end data management, and integration of Artificial Intelligence (AI) for process efficiencies. led successful process improvements and developed enterprise-wide BI solutions. A collaborative leader, excel in managing projects and driving innovation in data-driven, and AI-Powered decision-making.
Artificial Intelligence: apply knowledge of AI practices and hands-on skills in supervised/unsupervised machine learning, Deep Learning and more
Data Architect/Engineering: Conceptual, logical and physical data modeling, ETL, data visualization, Big Data analysis, Cloud Computing (MS Azure, Synapse and data lake, Lakehouse, Eventhouse),
Data Modeling and Statistical Analysis: GLM/Logit/Probit, Survival Data Modeling (Cox/kaplan-meier), Linear regression analysis, Logistic regression, cleaning verification Samples, Hypothesis Testing, analyzing and reporting data and findings, summarizing data from meaningful data comparisons, scientific documentations
Health Information Management: Manual and automated HIT, EHR (Epic), ERP (Lawson, workday) (management, analysis and use of health care data for decision making, design, implementation, and analysis of EHR
Leadership and Management: Kaizen Leader, excellent resource (Time, Human, Financial) management skill, proven track of leadership skill, ability to managing Multiple projects simultaneouslyEnterprise information architecture
Business intelligence Solutions(Datawarehouse design and implementation, ETL, Data Visualization
Microsoft Certified: Fabric Data Engineer Associate, (DP-700):
Artificial Intelligence Engineer Practitioner, Booz Allen Hamilton:
· Skills: apply knowledge of AI practices and hands-on skills application, which results in in-depth knowledge and intermediate demonstration of skills. This role is targeted toward working in data science roles, software engineers, data analysts, advanced data scientists, and others in data utilization.