Data Science & Analytics Leader
Detail-oriented and results-driven professional with 16 years of experience building and scaling advanced analytics, machine learning, and data engineering solutions across biomedical research, semiconductor manufacturing, entertainment, and hospitality.
Recent Focus: Completed advanced training in LLM engineering and agentic AI systems. Continuing exploration of agent-based modeling methodologies, including epidemiological simulation in Julia and performance benchmarking of ABM frameworks.
Areas of Expertise
- Data Science Leadership — Building and mentoring high-performing analytics teams
- Advanced Analytics — Statistical modeling, simulation, forecasting, and optimization
- Machine Learning — Deep learning, anomaly detection, predictive modeling
- Data Architecture — Lakehouse design, cloud platforms, MLOps
Featured Projects
LSTM-Based Anomaly Detection for Checkout System Monitoring
Developed a deep learning anomaly detection system to proactively identify checkout system degradation before guest-facing outages occur, combining LSTM autoencoders with statistical process control.
View project →Agent-Based Marketing Mix Simulator for COVID-era Planning
Designed and implemented an agent-based simulation model to preserve marketing mix optimization capability when COVID-19 rendered traditional regression models unusable due to structural breaks in historical data.
View project →Live Cell Tracking in Oscillating Intensity Images
Designed and implemented a novel computer vision system for tracking biological cells in microscopy images with time-varying intensity, using particle filters, optical flow, and finite elements simulation. 25,000 lines of cross-platform C++.
View project →Technical Explorations
- Agent-Based Modeling: COVID-19 epidemiological simulation and ABM framework performance comparison (Julia vs Python)
- Recent Training: LLM Engineering & Agentic AI — Udemy, 2025
Contact
- Email: kevin@dehoff.me
- LinkedIn: LinkedIn
- GitHub: GitHub