Experience

Data Scientist – Kiewit Corporation

April 2024 – Current

Researched and developed data science solutions across construction safety, scheduling, estimating, cost forecasting, productivity, and project performance
Built machine learning models for safety risk forecasting, productivity prediction, cost-risk analysis, and schedule-based project performance monitoring
Supported a range of analytics projects, including safety risk forecasting, schedule deterioration analysis, estimating intelligence, indirect cost benchmarking, and craft overrun modeling
Translated model outputs into business impact through risk ranking, overrun estimation, peer-group benchmarking, and executive-level reporting
Developed and maintained production-ready data pipelines and model workflows using Azure, Databricks, Dagster, Python, and SQL
Communicated findings through dashboards, visualizations, reports, and stakeholder presentations to support data-driven decision-making

January 2017 – May 2024

Trained machine learning models with 98% accuracy, an improvement by 10% in comparison to state-of-the-art, in structural health monitoring
Collaborated with engineers, bridge managers, and researchers to develop and implement machine learning and deep learning models for prediction of bridge maintenance, resulting in 3 research publications and other ongoing work
Created web crawlers for scraping environment, population, and inspection records resulting in a collection of over 21 million records
Communicated results analysis through interactive visualizations, written reports, publications, and presentations