Professional Experience

H.E.B, Inc. – Senior Data Scientist (February 2020 – Present)

  • Innovation in Forecasting: Spearheaded the development of a cutting-edge forecasting engine utilizing Ray and Vertex AI on GCP, alongside Dataform, achieving a significant 9% error reduction and a 15% reduction for promoted items. This innovation not only enhanced inventory efficiency by 5% but also set a new standard in predictive analytics within the retail sector.
  • Promotional Forecasting Transformation: Led a transformative initiative to migrate the promotional forecasting platform to PySpark, optimizing the logic and models on AWS. This pivotal project resulted in a 2% reduction in forecasting error and a nearly 70% decrease in runtime, demonstrating my capability to drive substantial efficiency improvements through technological advancements.
  • PipeLearner Development: Created and developed PipeLearner, a Spark-distributed package, which revolutionized model training and deployment processes, cutting down time by over 50%. This tool exemplifies my commitment to operational excellence and innovation in data science practices.

University of Texas at San Antonio – Research Assistant/Instructor/Teaching Assistant (2016 – 2019)

  • Educational Impact: Enhanced predictive accuracy in educational research through the application of advanced statistical and machine learning techniques, contributing significantly to the development of student success strategies.
  • Cybersecurity Advancements: Conducted groundbreaking cybersecurity research within a manufacturing context, employing a game theory approach that bolstered security measures and data protection protocols.
  • Operational Efficiency: Improved shop floor scheduling efficiency in a virtual manufacturing environment by utilizing sophisticated optimization algorithms, showcasing my ability to apply data science methodologies for operational enhancements.

Reef Chemical Industries Complex – Manufacturing/Enterprise Data Analytics Manager (2013 – 2015)

  • Predictive Maintenance Model Implementation: Developed and implemented predictive maintenance models that markedly improved operational efficiency and equipment lifespan, demonstrating my ability to leverage data science for tangible business improvements.
  • Data Infrastructure Development: Designed and established comprehensive data structures for operations tracking, significantly boosting data analysis productivity and informed decision-making capabilities.

Isfahan Steel Complex – Data Analyst/Consultant (2009 – 2013)

  • Maintenance System Optimization: Led the adoption of an optimized maintenance system, which played a critical role in reducing unplanned downtime and enhancing machinery health forecasting, underlining my proficiency in applying data analysis for operational excellence.
  • Emergency Maintenance Data Analysis: Employed statistical analysis techniques to scrutinize emergency maintenance data, achieving a notable reduction in emergency repairs and underlining the value of data-driven insights in crisis management and prevention.