Data Scientist

Romboost
(2024 - Actuality)

As a Data Science Intern at Romboost, I work closely with experienced data scientists and cross-functional teams to assist in the development and implementation of data-driven solutions. This role offers exposure to various aspects of data science, including:

• Software engineering.
• Data engineering.
• Data analysis.
• Machine learning.
• Statistical modeling.

Responsibilities:

Data Collection and Preparation:

• Assisted in collecting, cleaning, and organizing large datasets for analysis.
• Collaborated with team members to understand data requirements and ensure data quality.

---

Software Engineering:

• Helped the team follow software engineering best practices such as CI/CD.
• Automated scripts to retrieve data with API calls or other resources.
• Performed small/medium changes in existing pieces of software.

---

Data Analytics:

• Conducted exploratory data analysis to identify patterns, trends, and insights.
• Assisted in developing models to support business objectives.

---

Machine Learning Development:

• Supported the development and implementation of machine learning models.
• Worked on feature engineering, model training, and evaluation.

---

Data Visualization:

• Created clear and insightful data visualizations to communicate findings to both technical and non-technical stakeholders.
• Collaborated with team members to design and present data-driven insights.

---

Documentation and Reporting:

• Documented methodologies, data sources, and model specifications.
• Prepared regular reports summarizing analysis results and key insights.

---

Web Application Development.

Clannish FX: Trading Academy
(2023 - Actuality)

A web application was developed focused on the internal processes of the academy. internal processes of the academy. The characteristics of this application were:

New customer registration automation.

PowerBI dashboard with real-time value insights.

Automation of email marketing strategies for customers not yet enrolled.

Security layer for the Academy database with cloud backup services.

Implemented technologies:

Python (Pandas, Numpy).

Excel.

MySQL.

PowerBI.

Docker.

HTML, CSS, JavaScript.

Cloud Computing (Azure, AWS y Render).

PC Part Assistant Application Development.

La Pasarela Technological Mall
(2020 - 2022)

An application was developed for the selection of computerscustoms in the shopping center La Paserala Cali. The characteristics of this application were:

Automation in component selection guaranteeing compatibility.

Optimization of the component selection process prior to assembly.

Increased customer satisfaction due to customized design for specific needs.

Implemented technologies:

Python (Pandas, Numpy).

Java.

HTML, CSS, JavaScript.

MySQL.