Position: Data Scientist
Category: Data Science
English level: fluent
Years of experience: 1


Joined the Machine Learning and Data Science research team, majoring in CNN, computer vision, and object detection techniques. I 
was responsible for collecting and preprocessing the dataset, creating, training, evaluating, and deploying the models. Being in a 
Research and Development department, I was able to research different architectures and interact with some, such as VGG16 for image 
classification and YOLOV5 for object detection. 
Achievements: 
•
Developed models integrated into a system to assist farm managers and farmers predict the crop and disease type for crops such 
as tomatoes, cabbage, maize, rice, sugarcane, and wheat and give possible solutions.
Developed a database to store user input, the analysis given and the time the analysis was done using PostgreSQL. This 
information was rendered to the user in a table format for future reference. 
•Processed the data at scale (including writing scripts, calling APIs, writing SQL queries, etc.) into a form suitable for analysis 
then consolidated it into a data platform for consumption by advanced analytics initiatives. 
 
•Developed and automated metrics, dashboards, and reports for data visualization as per the user's analysis. 
 
•Developed and maintained technical documentation/manuals on configurations, setups, and deployment of the solution.

Dockerized web scraping application using Celery, Python (Django) to obtain cyclone tracking information. This information 
is scheduled to run periodically using a Redis queue and stored in a PostgreSQL database. Running the application and containers using the Docker-Compose file.