Friendly analytics, AI tools, and decision-ready data stories
I build thoughtful data products, forecasting systems, AI workflows, and dashboards that help people make clearer decisions.
Project Garden
Choose a tile. Follow the story.
Workflow Systems
AI Automation
Smart tools that reduce manual work and help teams move faster.
Time Series
Forecasting
Forecasting pipelines that help leaders understand what may happen next.
Product Build
Inventory SaaS
A mobile-friendly inventory tracker for event and venue businesses.
Object Detection
Computer Vision
Shelf-space detection model trained to identify empty retail shelves.
Experimentation
A/B Testing
Practical experimentation thinking for business and healthcare decisions.
Decision Support
Dashboards & Storytelling
Dashboards and narratives that turn data into business clarity.
Computer Vision Project
Retail Shelf Stockout Detection
During her Master's program at UTSA, Lauren led a 12-person team in developing an award-winning computer vision system capable of detecting empty shelf space in retail stores using YOLOv4 object detection. From coordinating data collection and managing image annotation to training models and presenting results, she oversaw the project from concept to deployment. The project received UTSA's Outstanding Project Non-Thesis Award and now serves as an example of how machine learning can transform a common business problem into an actionable, scalable solution. Explore the case study, model artifacts, comparison results, and live demo to see the project in action.
- 🏆 Outstanding Project Non-Thesis Award
- 👥 Led a 12-Person Team
- 🖼️ Thousands of Manually Annotated Images
- 🎯 Custom YOLOv4 Object Detection Model
- 🛒 Real Retail Shelf Data
- 🚀 Live Inference Demo Available
Quick Stats
Model
YOLOv4
Annotation Tool
LabelImg
Label Format
YOLO
Class
EMPTY
Deployment
Streamlit Cloud
Project Type
Applied Computer Vision
Demo Video
Model Comparison Demo
Archived model comparison video from the original project.
Live Demo
The live Streamlit app loads preserved model artifacts and runs inference on selected or uploaded shelf images. No retraining occurs in the demo.
Try the Live Detection AppResults / Impact
- Detected empty shelf regions across varied retail shelf layouts
- Demonstrated object detection on visually noisy, real-world shelf images
- Compared YOLO-based approaches during experimentation
- Built an interactive inference experience for portfolio demonstration
- Awarded the Outstanding Project Non-Thesis Award from the University of Texas at San Antonio plus a $2,000 stipend for her leadership, accuracy, and innovation during this time-critical project
What I Would Improve Today
- Add formal experiment tracking with MLflow or similar tooling
- Preserve complete training metadata and dataset versioning
- Add precision, recall, mAP, and confusion matrix reporting
- Improve annotation QA and labeling guidelines
- Compare modern YOLO versions under a reproducible pipeline
- Package model artifacts with a more production-ready deployment strategy
Experience Timeline
More than a resume.
Associate Data Scientist
Government Employees Health Association (GEHA)
Building forecasting, analytics, and decision-support systems within a complex healthcare data environment. Focused on creating scalable analytical workflows, improving business visibility, and translating data into actionable insights for leadership.
President
Business & Professional Toastmasters
Leading club operations, mentorship initiatives, and member engagement efforts while modernizing communication and reducing manual administrative processes through lightweight automation and structured systems.
Founder / Builder
Data by Lauren
Creating AI productivity tools, interactive portfolio projects, and practical analytics systems focused on helping small teams make clearer decisions and operate more efficiently.
Data Science Instructor
Codeup
Delivered immersive data science instruction for adult learners transitioning into technology careers, covering Python, SQL, statistics, machine learning, and real-world analytical problem solving.
Data Scientist I
Limeade (WebMD Health Services)
Worked on the Personalization team within the wellness-tech space, supporting recommendation systems, experimentation efforts, and behavioral analytics designed to improve user engagement and in-app experiences.
Operations Administrative Assistant
E Controls
Automated reporting and audit workflows while supporting operational improvement initiatives. Also developed internal marketing materials and safety messaging that were implemented across the engineering production floor.
Tutor
University of Texas at San Antonio — Center for Professional Excellence
Discovered a passion for mentorship and technical education by supporting students in analytics, statistics, and data science concepts through individualized instruction and guidance.
Outstanding Project Award Recipient
University of Texas at San Antonio — Alvarez College of Business
Received the Outstanding Non-Thesis Project Award plus a $2,000 stipend for leading a computer vision project focused on detecting retail shelf stock-outs using deep learning and object detection techniques for a major grocery retailer.
Undergraduate & Graduate Student
University of Texas at San Antonio
Returned to college as a non-traditional student with renewed focus and discipline, graduating near the top of the class and earning recommendation into an accelerated Master's program in analytics and data science.
Loan Officer
Check Into Cash
Developed early experience in financial operations, customer interaction, and lending analysis while gaining firsthand perspective on the ethical impact financial systems can have on vulnerable communities.
Who I Am
Data scientist. Curious builder. Systems thinker. Storyteller.
I like turning messy information into tools, stories, and systems that make work clearer. My sweet spot is where analytics, product thinking, and practical automation meet.
Previously connected to work across
HealthcareRetailEngineeringForecastingDashboardsCommunity Leadership
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