Sebastián Quesada Centeno

Electronic Engineer with experience in hardware and software development and validation. I am interested in the field of Data Science and want to develop more experience in this field. I consider myself as an empathetic, persevering, responsible, and flexible person.

(September 2019 - Now) Product Development Engineer, Componentes Intel de Costa Rica.

Duties/Responsibilities

• Work with various design teams from the initial IP product planning phase through design implementation, and verification.
• Experience defining test methodologies for different areas, including voltage and current consumption, and data feed forward between different phases of the unit’s tests.
• Familiarity with the usage of C Sharp to implement a code service for the different design teams, to help them with the data forwarding of their tests between the different stages of the unit’s testing. Each function of the service, had the respective unit test and a simulation of a real case scenario that ran in a Github pipeline.
• Experience analyzing and evaluating component specification versus performance to ensure optimal match of component requirements with production equipment capability.
• Data analysis of multiple types of tests to detect behaviors in the units and possible errors within the tests, including the extraction and cleaning of data from databases via simple SQL codes from tools such as Python, Excel, and JMP.
• Management of usage daily/weekly syncs to oversee the status of team’s tasks.

Duties/Responsibilities

• Work with various design teams from the initial IP product planning phase through design implementation, and verification.
•  Development of simple python codes for task automation (e.g., parsing of Excel files).

(2021 - 2022) Data Science Program (Academic specialization), Technological Foundation of Costa Rica (FUNDATEC), Cartago, Costa Rica.

Duties/Responsibilities

• Implementation of different machine learning algorithms, such as naive bayes classifier, decision tree, random forest, and simple neural networks to accomplish different classification tasks.
• Manipulation (concatenation, union, and cleaning of data) of different datasets to obtain a larger and more varied dataset in characteristics.
• Use of unit tests in PySpark to verify functions worked as expected.
• Application of Tableau to visualize data previously processed in tools such as RStudio or Jupyter Notebook.

Graduation Proyect

• Implementation of a banana plant detector on RGB orthomosaics, through the use of the free use algorithm, You Only Look Once (YOLO).