Daniel Alfonso Email and Phone Number

Developed and deployed Python and SSIS scripts for scheduled ETL processes, automating data extraction, transformation, and loading for RMS's Financial Services analytics platform, resulting in enhanced data flow efficiency and reduced manual errors.Applied data science methodologies, including logistic regression, to analyze SQL task scheduling data, uncovering critical KPIs that led to a more than 10% reduction in failure rates. Presented these findings to senior management, driving improvements in operational strategies.Enhanced the efficiency of scripts by over 30%, streamlining data workflows and significantly reducing processing time.Led the data cleaning and transformation project, processing over 10 million rows of raw data from multiple restaurant locations across 30+ states.Directed the creation of dimension tables to establish a comprehensive relational database structure, ensuring data integrity through the application of data modeling principles, including third normal form (3NF) normalization.

Led a pioneering analysis of fugitive hydrogen emissions within transportation and storage systems, generating valuable insights into leak quantification.Created advanced Excel models to evaluate technical parameters, CO2 equivalent emissions based on Global Warming Potential (GWP), and safety considerations of hydrogen leaks, aiding in the identification of optimal engineering solutions for the hydrogen supply chain.Devised and implemented strategies to mitigate the climatic impact of hydrogen by minimizing its indirect GWP of 11.6 through improved containment measures and reduced atmospheric leakage.Gained in-depth knowledge of hydrogen storage dynamics and leakage rates, conducting thorough research and analysis to inform best practices.