Francis Smart

Francis Smart is a seasoned data scientist and qualitative researcher with nearly two decades of experience specializing in data strategy and analytics. Throughout his career, Francis has demonstrated expertise in data-driven decision making, operational improvement, and strategic planning. He is adept in data engineering, data science, software development, and statistical analysis. His proficiency extends across various programming languages and tools, including Python, PySpark, R, Stata, and SQL, which he leverages for data preparation, predictive modeling, and data visualization.

In his current role as a Senior Data Scientist at Censeo Consulting Group, Francis supports operations and innovation efforts for civilian government agencies, focusing on data management and analytics to improve acquisition program effectiveness. His contributions span projects involving infrastructure optimization and process improvement, where he routinely engages in stakeholder consultations and proposes new data management strategies and metrics.

Francis has also played a pivotal role in several federal and nonprofit projects, where his efforts have resulted in enhanced adoption of new technologies such as machine learning and large language models. Beyond his professional commitments, he has been a dedicated volunteer, serving as a treatment foster parent and contributing to nonprofit initiatives.

Francis attended Montana State University, where he earned both his Bachelor of Science and Master of Science degrees in Economics, graduating with honors. Currently, he is graduating with his Ph.D. in Measurement and Quantitative Methods at Michigan State University in 2024. His academic accolades include an IES university level competitive fellowship as well as an ORISE fellowship to support his research endeavors with the Department of Transportation.

With his strong background in data analysis, statistical strategies, human capital strategy, and performance metrics, Francis Smart continues to drive valuable insights and implementation support for improving vendor behaviors leading to increased performance and cleaner data.