Earlier insight. Better allocation.
Risk prediction, cost reduction, capacity forecasting, and preventive decision support.
Business Analytics Professional
Turning data into strategic decisions.
I apply artificial intelligence, predictive analytics, and business intelligence to complex challenges in healthcare, finance, and organizational strategy.
Artificial IntelligenceHealthcare AnalyticsFinancial Analytics
4End-to-end analytics projects
3Professional focus areas
15+Models and analytical methods
1Mission: measurable impact
01 / About
Analytics with a business purpose.
I am a business analytics professional focused on transforming complex data into clear, practical decisions. My graduate work combines machine learning, forecasting, optimization, data visualization, and executive communication across healthcare and financial applications.
My work is guided by one principle: an analytical model is most valuable when it helps people act. I build solutions that connect technical rigor with operational efficiency, financial performance, and meaningful outcomes.
Evidence for smarter strategy.
Financial modeling, market signals, forecasting, performance analysis, and risk interpretation.
Models designed for action.
Machine learning, predictive analytics, explainability, validation, and optimization.
Clarity for decision-makers.
Dashboards, KPIs, data storytelling, executive reporting, and strategic recommendations.
Selected portfolio
Four projects. One clear professional direction.
Each project moves from a real business problem through data preparation, modeling, validation, interpretation, and actionable recommendations.
01
Finance · NLP · Predictive Modeling
Stock Return Prediction Using Financial Metrics and SEC Filing Text
Evaluated whether numerical language features extracted from SEC filings improved stock-return prediction beyond traditional financial metrics. The project compared financial-only, text-only, and combined model pipelines with chronological validation.
- OLS baseline and robust interpretation
- Financial text features and sentiment signals
- Time-aware validation and feature selection
02
Healthcare · Classification · Prevention
Early Diabetes Risk Prediction Using Machine Learning
Developed classification models using the CDC BRFSS health indicators dataset to identify individuals at elevated diabetes risk and support earlier preventive intervention and resource allocation.
- Logistic Regression, Random Forest, and XGBoost
- Class imbalance and false-negative analysis
- Healthcare-focused model interpretation
03
Healthcare Finance · AI · Cost Reduction
Predicting Preventable High-Cost Patients Before Crisis Care
Used the MEPS 2022-2023 longitudinal dataset to predict future high-cost healthcare status from prior-year health, utilization, insurance, socioeconomic, and expenditure information.
- Random Forest sealed validation ROC-AUC: 0.817
- Top-decile lift: 4.31
- Risk segmentation and preventive-care workflow
04
Healthcare Operations · Forecasting · Optimization
Optimizing Hospital Resource Allocation Using Artificial Intelligence
Built an end-to-end decision-support framework using CDC/NHSN weekly hospital data. XGBoost forecasts next-week inpatient occupancy, while a linear optimization model recommends surge-bed and staffing adjustments.
- XGBoost average R²: 0.907
- Average RMSE: 2.888 occupancy points
- Forecast-to-action optimization framework
02 / Expertise
A multidisciplinary analytics toolkit.
Programming & Data
Python, SQL, Excel, data cleaning, feature engineering, statistical analysis, reproducible workflows.
Machine Learning
Linear and logistic regression, Random Forest, XGBoost, model validation, feature importance, calibration.
Business Intelligence
Power BI, Tableau, dashboards, KPI design, data visualization, executive reporting, decision support.
Applied Analytics
Healthcare analytics, financial analytics, forecasting, optimization, cost-benefit analysis, resource allocation.
PythonSQLPower BITableauExcelXGBoostRandom ForestForecastingOptimization
Research and professional development
Building a focused body of work.
Predictive Analytics for Diabetes Risk
Machine learning for earlier identification and preventive resource allocation.
Predictive Analytics for Healthcare Cost Reduction
Identifying future high-cost patients before preventable crisis utilization.
Artificial Intelligence for Hospital Resource Optimization
Forecasting demand and translating prediction into staffing and bed-allocation decisions.
AI, Healthcare, Finance, and Responsible Decision Support
Developing practical frameworks that connect analytics performance with business and societal impact.
My goal is not simply to build models.
It is to build analytical solutions that improve how organizations decide, allocate, and grow.
Let’s connect
Interested in analytics, healthcare innovation, finance, or strategic decision support?
I welcome conversations with recruiters, analysts, researchers, healthcare leaders, finance professionals, and organizations working on meaningful data-driven challenges.