Hi, my name is
Kent Bourgoing
Data Scientist & AI/ML Engineer
UC Berkeley master’s graduate passionate about building data science and AI/ML systems for real-world impact.
About Me
I’m Kent Bourgoing, an AI Engineer at OneMagnify and a graduate of UC Berkeley’s Master of Information and Data Science (MIDS) program. I earned my undergraduate degree in Chemical Engineering from UCLA, which gave me a strong foundation in structured problem-solving, quantitative thinking, and technical communication.
My path into AI and data science started with an interest in using data to solve real-world problems. Through the MIDS program, I built end-to-end projects across machine learning, NLP, LLM applications, causal inference, time series, scalable data processing, and ML deployment. I enjoy turning messy, real-world data into practical models and tools that help people make better decisions.
Before joining OneMagnify, I worked as an engineering consultant, where I developed strong experience in client communication, technical analysis, and delivering work in complex, real-world environments. That consulting background continues to shape how I approach AI engineering: understand the problem clearly, communicate tradeoffs, and build practical solutions.
Today, I’m focused on applied AI, machine learning engineering, NLP/LLM applications, and production-ready AI systems. I’m especially interested in building AI tools that are useful, reliable, and connected to real business needs.
Outside of work, I enjoy watching soccer, playing tennis, and exploring new cities through travel.
Technical Skills
Tools I use to build end-to-end data solutions, from analysis to production deployment.
Featured Projects
Projects ranging from statistical analysis and experiments to deployed AI/ML systems.
AI-Powered Legal Citation Analyzer
Client capstone with Wolters Kluwer: Agentic RAG system using Neo4j knowledge graphs and multi-LLM orchestration to automate legal precedent research.
English Text Detoxification System
Modular NLP system that rewrites toxic content into safe alternatives using explainability-driven masking and multi-objective reranking.
End-to-End ML API on AWS EKS
Production-grade ML inference API with Redis caching, Kubernetes HPA autoscaling, and Istio service mesh on AWS EKS.
Reducing Child Accident Risk
Randomized controlled field experiment quantifying causal effect of visual interventions on driver behavior in residential zones.
Flight Delay Prediction at Scale
Scalable ML pipeline on Databricks integrating 28M flights + 131M weather records with blocked time-series cross-validation.
Heart Failure Survival Prediction
Clinical ML system predicting patient survival using GMM-based synthetic augmentation and ensemble classifiers.
Atmospheric CO2 Forecasting
Time series analysis of Keeling Curve data with ARIMA/SARIMA modeling and 26-year forecast validation.
Labor Economics Analysis
Econometric analysis of 69K+ Census records quantifying the marginal return to work hours using log-linear regression.
Bay Area Delivery Optimization
Polyglot persistence architecture combining PostgreSQL analytics and Neo4j graph algorithms for last-mile delivery optimization.
Get in Touch
Have a question, opportunity, or collaboration in mind? Feel free to reach out.