Guillermo Luque

Feature extraction and data presentation in dashboards managed by Tableau. Implementation of machine learning-based algorithms on big datasets using PySpark and ML to predict retail return probabilities. Development of Databricks workflows to perform analytics on streaming datasets using Delta Lake architecture. Extract structured tidy data from unstructured text logs.

Discovered meaningful patterns on biological datasets greater than 1 TB using statistical machine learning and different data analysis workflows including Apache Spark, MLflow, Tensorflow, R, Python, and Julia. Designed and deployed these workflows on both high-performance clusters (GPU computing) and Amazon AWS using Docker and Kubernetes.

Transformed two flagship products to take advantage of big data analysis, machine learning, and cloud computing, lowering development costs and increasing revenue by 100%. Used machine learning to detect anomalous transactions by including approximately 1 TB of non-structured client information. Designed and implemented orchestration routines for their deployment in Microsoft Azure Oracle Cloud, and Amazon AWS depending on bank choices. Developed financial core algorithm using Python and C++.

Implemented and established new web-based vendor recommendation system, eliminating paper usage in requisitions approval by 90% company wide.

Managed development of recommendation mobile platform for retail sector to handle over 100 sessions per minute, using optimized search algorithms.

Designed and led the development of the company's ERP system, integrating the company's country-level operation. Established ETL pipelines using R and Apache Spark to extract key factors from almost 2 TB of accounting, human resources, and financial historical records.

Designed and lead the implementation of the company's ERP system from the integration of applications that I had previously developed for the accounting and commercial management areas.

Built the software for the analysis of inertial signals collected by an intelligent device during the inspection of hydrocarbon transport lines, as part of the SCADA services provided by the company. Implemented a 3D model of the behavior of the device inside the line, based on the analysis of the collected signals, as well as a geo-location software to simulate the inspection trajectory of the device.

Established firewalls and main networking services to support distribution of Internet access services for 5000 customers.

Developed and initiated projects, managed costs, and monitored performance of web applications for manufacturing sector. Increased revenue by 30% using open-source software (PHP/PostgresQL).

Waiting for certificates between June/July 2023