Kenneth M.
Data Scientist

Skills

Sql

Python

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Bio

Data Analyst with five years of professional experience, including four years concentrated on data analysis within Communication, Logistics, and Administration sectors, as well as direct involvement with security for the terrestrial segment of the Brazilian Armed Forces. Expertise in identifying insights to drive business decisions and proficient in data manipulation using Python libraries such as Seaborn, Pandas, Numpy, Matplotlib, and Streamlit. Adept in database management, ensuring data integrity and facilitating the extraction of meaningful information.

Capabilities include statistical analysis and data modeling to identify patterns, trends, and opportunities for business process improvement. Experienced in building, evaluating, and implementing machine learning models using Scikit-Learn and TensorFlow, focusing on prediction, classification, and process optimization.

Expertise follows the CRISP-DM methodology, adheres to LGPD norms, and utilizes Git for project versioning. Proficient in Linux and Big Data environments. Advanced practical knowledge of the Microsoft Office suite, with four years of experience in Excel and Access, and familiarity with tools such as Power BI, SQL, and Spark for dataset management.

Captain
3/1/2019 - 2/1/2024

Achieved coordination of the EXAR project, effectively managing the national database of reservists and overseeing the risk management of the Mobilization Section. This involved preventing execution failures and conducting comprehensive data analysis to identify patterns and trends, thereby optimizing operational efficiency. Managed documentation for discharged personnel with rigorous compliance to established procedures, ensuring precise and up-to-date records aligning with LGPD standards for future data analysis and insights.

Developed a Python script to extract specific data from the SERMILMOB system, resulting in a 65% increase in presentations over three years. This initiative enhanced the efficiency of processes and improved communication with reservists, utilizing Python's robust data analysis and manipulation capabilities.

Oversaw the Personnel Section, focusing on documentation and processes for incorporated personnel such as Corporals and Soldiers. Conducted promotions and courses while coordinating the allocation and reallocation of temporary military personnel across various sectors, ensuring an equitable and effective distribution of human resources. This management was informed by data analysis to identify needs and opportunities for continuous improvement.