Juan Felipe Parra Patino

I am a bilingual (English C1) Electronic Engineer with experience as an intern Data Scientist in the hydroelectric industry. I have a solid background in mathematics, statistics, and programming, implementing Machine Learning (ML) algorithms using programming languages such as Python, R, and Java. I am proficient in Microsoft Office tools (Excel, Power BI) and DBMS (MySQL, MongoDB, SQLite), as well as frameworks like Django, FastAPI, and TensorFlow. Additionally, I have knowledge in data analysis, predictive modeling, data mining, and data visualization using agile methodologies such as Scrum. I am characterized by my strong problem-solving skills, effective communication and presentation abilities, and experience collaborating with multidisciplinary teams and data projects. I am seeking a challenging opportunity to apply my skills and knowledge.

Functions:

Collect and clean data from different sources and databases for the application of algorithms that enable the analysis and identification of performance and criticality of company assets, using tools such as MySQL, Python, and Power BI.
Develop and maintain data pipelines and ETL processes for efficient integration of data, and perform exploratory data analysis to identify patterns and anomalies in asset performance data using Python and SQL.
Evaluate and select suitable machine learning models and techniques, using Python for criticality analysis.
Achievements:

Increased efficiency by approximately 80% in the extraction, transformation, and loading (ETL) process through the development of a Python script that automates the process.
Implemented machine learning algorithms to analyze and identify the performance and criticality of company assets using Python, also creating visualizations and reports in Power BI to communicate criticality assessments to stakeholders.
Improved the accuracy of asset performance analysis by approximately 80% through optimization and enhancement of existing algorithms.
Successfully identified high-risk assets, enabling proactive maintenance and reducing unplanned downtime.
Contributed to cost savings by identifying underperforming assets and recommending optimization strategies.

bachelor´s degree in electronical enginering
google data analytics professional certificate
IBM machine learning professional certificate