Briant Moreno
Data Scientist Learner
Data Scientist
Technical Skills: Python (pandas, numpy, scikit-learn, matplotlib, seaborn), SQL (MySQL), ML (regression, classification, clustering)
Education
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Bootcamp, Data Science Tripleten (December 2025) -
B.S., Nanotechnology Engineering Instituto Tecnologico y de Estudios Superiores de Occidente (ITESO) (December 2020)
Work Experience
Triage Engineer @ Concentrix Catalyst (March 2025 - Present)
- Monitoring multiple applications for a telecommunications company.
- Ensuring system stability by performing incident triage/management and error alert monitoring, log analysis and troubleshooting.
- Coordinating solutions with development teams to improve system performance in production environment.
Production Support Technical Lead @ Tata Consultancy Services (TCS) (June 2020 - March 2025)
- Leading and mentoring a team of engineers to ensure system stability by establishing best practices for monitoring, debugging, and incident response.
Production Support Specialist @ Tata Consultancy Services (TCS) (February 2021 - June 2022)
- Monitoring and supporting multiple applications across web, mobile, and executive banking platforms.
- Ensuring system stability and operational efficiency by managing day-to-day operations, performing incident triage/management and error alert monitoring, log analysis and troubleshooting.
- Coordinating solutions with development, management, and business teams to improve system performance in production environment.
Projects
ML model to predict the amount of gold extracted from gold ore for the heavy industry (2025)
Analyzed and cleaned the data from extraction and purification processes of gold ore to developed a machine learning model to predict the final amount of gold obtained. Achieved a final sMAPE (symmetric mean absolute percentage error) score of aprox. 0.76 in gold amount predictions.
ML model to predict the customer cancellation rate for a telecommunications operator (2025)
Analyzed and cleaned personal customer data from a telecommunications operator to developed a machine learning model to predict the customer cancellation rate. Achieved a final accuracy score of aprox. 0.85 in customer’s cancellation rate prediction.