Hello, I am
CamelliaLe
Early-career data professional passionate about bridging the gap between data and business strategy.
About Me
I'm Camellia — a graduate student in Artificial Intelligence and Business Analytics, focused on transforming complex data into actionable insights. With a strong foundation in data analytics, machine learning, and data engineering, I enjoy working across the full data lifecycle, from building data pipelines to creating dashboards and models. My goal is to turn analysis into clear, meaningful recommendations that drive impactful business decisions.
Through my internships and projects, I've applied data to real-world business challenges, always focusing on practical outcomes and usability. I've also been involved in AI and cybersecurity research, which has shaped my interest in building thoughtful, real-world solutions.
Research
Enhancing Cloud Security Assessment Frameworks for the Generative AI Era: An Action Design Research Approach
Pourbehzadi, Motahareh; Le Nguyen Huong, Tra; Javidi, Giti; Luthra, Anita
Projects
- Developed ETL workflows to process and validate CMS healthcare data, transforming raw datasets into structured fact and dimension tables for analysis.
- Built SQL analyses and Tableau dashboards to evaluate hospital performance, uncovering insights on profitability, cost efficiency, and regional trends to support business decision-making.
- Processed and analyzed a 3M+ token dataset using Python and SQL, applying exploratory data analysis and model evaluation to improve response accuracy to 85%.
- Developed end-to-end data and analytics pipelines for ingestion, inference tracking, monitoring, and optimization, reducing latency by 75% and infrastructure costs by 82%.
- Developed automated data analytics pipeline to collect, clean, validate, and process 1,000+ new internship postings daily, delivering insights to hundreds of students.
- Applied automated classification models (GPT-4o, Google Gemini) to categorize job data and filter low-quality entries, increasing pipeline efficiency by 90%.
- Integrated 10+ global datasets in Tableau to analyze AI and labor trends, identifying a 2,700% growth in generative AI investment.
- Developed dashboards using calculated fields and trend analysis, revealing a 25% drop in worker confidence despite AI hiring expansion.
- Evaluated automation risk across occupations, highlighting 48% exposure in routine jobs and uneven regional workforce impact.
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Experience
Graduate Research Assistant
University of South Florida
Conducting research on AI safety and cybersecurity, developing attribution-based methods to analyze authority bias in large language models. Co-authored "Enhancing Cloud Security Assessment Frameworks for the Generative AI Era," a peer-reviewed paper awarded Best Paper Runner-Up at AMCIS 2025.
Sales Analyst Intern
TeamViewer
Processed and validated large datasets using Excel and SQL for initial analytics, then visualized key sales trends through Power BI and Tableau dashboards. Created Excel VBA automation to reduce processing time by 40% and minimize errors.
Research Analyst Intern
Resilience Inc.
Achieved a significant 30% efficiency improvement through advanced analytics utilizing Python. Aggregated and analyzed unstructured data from 1,000+ sources using SQL and Python to support downstream analytics.
Business Analyst Intern
VNDirect Securities Corporation
Assembled, cleaned, and transformed 50+ financial datasets using Python, improving data accuracy by 30% and reducing analysis time by 20%. Designed and managed daily security data dashboards using Tableau and Power BI.
Let's Connect
I'm always open to discussing new opportunities, data challenges, or interesting projects. Feel free to reach out!