Transforming business challenges into data-driven solutions with 3+ years of cross-functional analytical experience

Data scientist with business consulting background and entrepreneurial experience. I combine analytical expertise, operational leadership, and technical skills to build machine learning solutions that drive measurable business impact.

Background: Business analyst → Operations management → Data science, bringing real-world context to technical problem-solving.

Recent Achievements:

• ~90% accuracy on SVHN digit recognition with 38.6% parameter reduction
• Built facial emotion detection CNN achieving ~82% test accuracy
• Delivered targeted marketing strategies through 5M+ ride-sharing data analysis
• MIT Professional Education Applied Data Science certification (May 2025)

Machine Learning & AI

Data Analysis & Visualization

Development & Tools

SVHN Digit Recognition
CNN Optimization for Edge Computing Applications | ~90% Accuracy
Achieved ~90% accuracy with 38.6% parameter reduction through systematic experimental analysis - essential for deploying ML models in resource-constrained environments. Conducted comprehensive studies on model complexity, learning rate optimization, batch size impact, and AutoML hyperparameter tuning to maximize performance while minimizing computational costs.

Facial Emotion Detection
Customer Experience & Security Analytics | TensorFlow
Developed grayscale-optimized CNN achieving ~82% accuracy for real-time emotion recognition applications in retail analytics, customer service optimization, and security monitoring. Built lightweight, edge-compatible solution enabling cost-effective deployment across multiple business use cases.

Bikeshare User Analytics
Marketing Strategy & Customer Segmentation | R Programming
Analyzed 5M+ ride-sharing records to identify usage patterns between member and casual rider segments. Delivered targeted marketing strategy including user-specific promotions, enhanced member benefits, and membership ranking system to drive customer acquisition and retention.

HR Analytics Dashboard
Workforce Planning & Attrition Prevention | Power BI
Built comprehensive dashboard analyzing 6M+ HR data points to predict employee attrition and optimize workforce planning. Implemented advanced DAX calculations and row-level security, enabling data-driven decisions for talent retention and organizational restructuring.

• Applied Data Science - MIT Professional Education (2025)
• Data Analytics Professional - Google (2024)
• Power BI Data Analyst Associate - Microsoft (2024)
• MBA, Finance Concentration - La Sierra University
• BA Business Management, Minor: Accounting - La Sierra University

Background: Business Analyst (DC consulting, $50M+ healthcare projects) → Operations Manager (restaurant industry) → Data Scientist. I leverage cross-functional experience and stakeholder management skills to deliver technical solutions with clear business impact.

Currently building: End-to-end production ML system demonstrating enterprise-scale capabilities.