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Gabriel Salazar
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Data Science Consultant | Electronics and Automation Engineer | Deep Learning, Neural Networks, Gen AI
Quito, Pichincha, Ecuador
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Résumé
Jobs
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SCADA EngineerPipecomMar 2026 - Current (8 months)- Data Science Consultant - Assistant IManagement SolutionsJul 2025 - Feb 2026 (8 months)Generando valor mediante analítica de datos, aprendizaje automático e inteligencia artificial en sectores como financiero, energético, tecnológico y otros. Mi enfoque está en transformar datos complejos en información accionable, permitiendo a las organizaciones tomar decisiones informadas y mejorar su desempeño. Como parte de un equipo de consultoría multidisciplinario, contribuyo al diseño e implementación de soluciones analíticas avanzadas adaptadas a las necesidades de cada cliente, siempre con énfasis en la confianza, la efectividad y el impacto medible. Nuestra misión es ser el socio de referencia, resolviendo desafíos críticos a través de estrategias basadas en datos que combinan innovación, rigor y ejecución práctica.
- WCM Performance Live EngineerSLBSep 2022 - Feb 2025 (2 years 6 months)• Led remote Measurement While Drilling (MWD) data acquisition, building scalable pipelines to ingest and process high‑volume sensor data (EMP, gamma‑ray, resistivity, sonic, pressure and mud‑pulse telemetry).
• Wrote Python scripts and SQL queries to integrate real‑time logs and automate data quality checks, supporting optimisation of wellbore trajectories.
• Designed dashboards and machine‑learning models to detect anomalies and predict equipment failures, reducing non‑productive time.
• Collaborated with cross‑functional teams across Latin America and the Middle East, providing training on new MLWD technologies and ensuring data quality.
• Applied machine learning and statistical methods to perform log interpretation - Maintenance InternGrupo BimboApr 2022 - Aug 2022 (5 months)• Developed data collection and ETL processes for manufacturing equipment using Python and MATLAB, enabling predictive maintenance analyses.
• Conducted exploratory data analysis and built statistical models to identify failure patterns and support preventive maintenance schedules.
• Created interactive dashboards in Power BI to monitor equipment health and operational KPIs, improving reporting efficiency.
• Collaborated with engineering teams to implement data‑driven maintenance strategies that decreased unplanned downtime and improved reliability. - Creative Research AssistantUniversidad San Francisco de QuitoDec 2021 - May 2022 (6 months)• Supported research projects in robotics and automation by developing software modules for data acquisition, signal processing and control.
• Conducted data analysis and simulations using Python and MATLAB to validate algorithms and contribute to academic publications.
• Collaborated with faculty and students to design and test prototypes, applying machine‑learning concepts to robotics tasks.
• Prepared technical documentation and assisted in writing research papers, ensuring clarity and accuracy. - Student InternSchlumbergerJun 2021 - Dec 2021 (7 months)• Extracted, cleaned and analysed large drilling datasets using Python and MATLAB; built Power BI dashboards to visualise failure patterns and support root‑cause analysis.
• Performed feature engineering and statistical analysis to develop predictive models for equipment performance.
• Integrated multiple data sources and KPIs to generate real‑time reports for engineering teams. - Research AssistantUniversidad San Francisco de QuitoSep 2020 - Jan 2021 (5 months)• Assisted research projects in electronics and control engineering, developing data acquisition systems, signal processing algorithms and control modules.
• Wrote Python and MATLAB scripts to automate data collection, cleansing and analysis for robotics and AI experiments.
• Collaborated with multidisciplinary teams to design, prototype and test embedded systems for automation and IoT.
• Contributed to publications by documenting methods, preparing figures and ensuring data accuracy.
Education
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- MIT Professional Education — Applied Data Science Program: Leveraging AI for Effective Decision-Making, Artificial IntelMIT Professional EducationJan 2024 - Dec 2024 (1 year)Data is getting created at a rapid pace. It is estimated that more than 2 quintillion bytes of data have been created each day in the last two years. As organizations experience an overflow of data, they are sparing no effort to extract meaningful insights to make smarter business decisions. In order to help you unravel the true worth of data, MIT Professional Education offers Applied Data Science Program, which aims to prepare data-driven decision makers for the future.
- Virginia Tech College of Engineering — Exchange Program, Ingeniería eléctrica y electrónicaVirginia Tech College of EngineeringJan 2019 - Dec 2020 (2 years)
- Universidad San Francisco de Quito — Electronic Engineer, Electrical and Electronics EngineeringUniversidad San Francisco de QuitoJan 2017 - Dec 2022 (6 years)