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Hi there! I'm Jaime Emanuel Cuero Lucero, a soon-to-be graduate in Computer Science with a focus on Data Science. I enjoy turning data into actionable insights and building cloud-ready solutions. I love writing about technology and collaborating with cross-functional teams to solve real-world problems. In my spare time, I work on side projects like a Streamlit app to classify rice grain varieties, contribute to the Computer Science Society as External Vice President, and share knowledge through monthly articles and labs.…Hi there! I'm Jaime Emanuel Cuero Lucero, a soon-to-be graduate in Computer Science with a focus on Data Science. I enjoy turning data into actionable insights and building cloud-ready solutions. I love writing about technology and collaborating with cross-functional teams to solve real-world problems. In my spare time, I work on side projects like a Streamlit app to classify rice grain varieties, contribute to the Computer Science Society as External Vice President, and share knowledge through monthly articles and labs.

Jaime Emanuel Cuero Lucero

Data Scientist, Web Developer, Full Stack Developer, +2

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Hi there! I'm Jaime Emanuel Cuero Lucero, a soon-to-be graduate in Computer Science with a focus on Data Science. I enjoy turning data into actionable insights and building cloud-ready solutions. I love writing about technology and collaborating with cross-functional teams to solve real-world problems. In my spare time, I work on side projects like a Streamlit app to classify rice grain varieties, contribute to the Computer Science Society as External Vice President, and share knowledge through monthly articles and labs.…Hi there! I'm Jaime Emanuel Cuero Lucero, a soon-to-be graduate in Computer Science with a focus on Data Science. I enjoy turning data into actionable insights and building cloud-ready solutions. I love writing about technology and collaborating with cross-functional teams to solve real-world problems. In my spare time, I work on side projects like a Streamlit app to classify rice grain varieties, contribute to the Computer Science Society as External Vice President, and share knowledge through monthly articles and labs.

Available to hire

Hi there! I’m Jaime Emanuel Cuero Lucero, a soon-to-be graduate in Computer Science with a focus on Data Science. I enjoy turning data into actionable insights and building cloud-ready solutions. I love writing about technology and collaborating with cross-functional teams to solve real-world problems.

In my spare time, I work on side projects like a Streamlit app to classify rice grain varieties, contribute to the Computer Science Society as External Vice President, and share knowledge through monthly articles and labs.

Skills

Experience Level

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Intermediate

Intermediate

Intermediate

Work Experience

IT Intern at Tutorials Dojo

October 1, 2025 - January 31, 2026

Developed and deployed a mobile application (AWS Mock Exams) on the Google Play Store to support cloud certification preparation. Built cloud-based application features using AWS best practices for scalability and security. Authored and published monthly technical articles about computing and technologies. Designed and documented hands-on GCP guide labs for practical cloud implementation. Collaborated with cross-functional teams to deliver technical solutions aligned with business needs.

External Vice President at Computer Science Society (CSS)

August 1, 2024 - May 31, 2025

Managed external communications between CSS and partner organizations to coordinate events and collaborative initiatives. Organized regular events to engage club members and connect them with industry professionals and club alumni. Worked closely with the executive officers to support the club’s outreach and logistical efforts.

Personal Project - Streamlit App at Self-Directed Project

September 1, 2025 - September 30, 2025

Designed, built, and deployed a Streamlit-based web application to classify rice grain varieties from image inputs. Developed and trained image classification model using the MobileNetV2 architecture, optimizing for accuracy and inference efficiency. Implemented image preprocessing and model inference pipelines to support real-time predictions within the web application. Conducted a research and feasibility study to evaluate model performance, dataset suitability, and deployment viability. Applied machine learning and computer vision techniques to solve an agricultural classification problem. Documented findings, methodology, and results to support reproducibility and future improvements.