Dave is a Data Scientist with over a decade of experience transforming complex datasets into actionable insights that drive strategic decision-making in finance, healthcare, and other data-rich sectors. Over the course of his career, Dave has led end-to-end analytical initiatives, from preparing and integrating large, siloed datasets to developing predictive models and designing intuitive visualizations that support informed decisions and operational improvements.

Dave has guided multidisciplinary teams in the design and implementation of reproducible workflows, robust data quality protocols, and standardized analytical methodologies. His work has contributed to reducing fraud, improving patient care, and enhancing efficiency in high-stakes environments where accuracy and accountability are paramount. Skilled in both traditional statistical analysis and modern machine learning approaches, Dave is adept at identifying patterns, uncovering trends, and translating complex technical findings into clear narratives for diverse stakeholders.

With a collaborative approach to problem-solving, Dave has mentored analysts and data scientists in Agile environments, fostering a culture of learning, innovation, and continuous improvement. His experience includes leading projects that integrate structured and unstructured data, develop classification and forecasting models, and deliver solutions that balance performance, interpretability, and regulatory compliance.

Dave holds a Master of Science in Business Analytics from The University of Scranton, an MBA in Finance, and a Bachelor of Technology in Engineering. He is certified as a Databricks Machine Learning Professional. He has also earned additional credentials in Alteryx, AWS Machine Learning, and Lean Six Sigma Foundations.