Nicolás Zamudio Franco

Data Analyst | Data Science | Business Management

About me

I am an administrator with a passion for data science and a desire for helping people to make their work easier and improve their decision making. I have knowledge in SQL, Python for analytics and data science (Machine learning and deep learning), and visualization (Pandas & Matplotlib, Power BI, Tableau, and Looker Studio). Additionally, I am in the process of improving these and more tools for data science.
Thank you for taking the time to learn more about me. I look forward to connecting and collaborating on exciting data-driven projects in the future!

Projects

Hotel sales analysis with Python and Tableau

This project integrates two key tools: Python for data cleaning, normalization, and transformation, and Tableau for data visualization and presentation. The dataset, sourced from Kaggle under the profile of Jesse Mostipak is first imported into Python for the EDA process and then exported for further use in Tableau.

See project

RESTful API for Posts with FastAPI and Render

I developed a RESTful API using FastAPI to manage blog-style posts, focusing on clean architecture and secure authentication. The backend was deployed to the cloud using Render, making the service accessible and easy to test. You can see the Live API Documentation Live API Documentation here
Technologies and tools used:
- FastAPI for building a high-performance, Python-based API with automatic data validation.
- SQLModel and SQLAlchemy as ORM tools for database modeling and query handling.
- Alembic for database version control and migration management.
- JWT (JSON Web Tokens) for user authentication and route protection.
- PostgreSQL as the relational database management system for data storage and retrieval.
- Render for cloud deployment of the backend in a production-ready environment., ensuring high availability and scalability.

FASTAPI documentation See project

Predictions on the stock market with LSTM networks (neural networks) in Python

Project based on LSTM networks to make the model handle long-term dependencies in sequential data in order to predict the next prices.
The neural network uses the Yahoo Finance pip library and the Nvidia shares.

See project

Automobile business analysis and supervised machine learning algorithms price prediction

This project realized the preprocessing, EDA and evaluates different regressor machine learning models to find the best one to predict the price of the cars.
This model uses the cars datasets of the University of California Irvine.
The algorithms used are Xgboost, polinomyal regression, SVM, Voting regressor, decission tree regressor and k-neighbors regressor.

See project

Mobile phones business analysis and supervised machine learning algorithms (price category prediction)

This project involves preprocessing, exploratory data analysis (EDA), and the evaluation of various machine learning classification models to determine the most effective one for predicting cellphone price ranges.
- Utilizing a Kaggle cellphone dataset, the model considers all available variables for prediction
- The algorithms implemented include XGBoost, Decision Tree, Random Forest, AdaBoost, and K-Neighbors Regressor

See project

Hackaton App for salary prediction

Contributed to a team project creating a web application that predicts starting salaries based on experience and desired position, while suggesting optimal countries for job applications. Personally handled the data science component, including data cleaning, preprocessing, analysis, and building the predictive model using Scikit-learn and Pandas. The application connects to the frontend through FASTAPI.
- The App is built in Vercel with Angular and here you can see the App Salary prediction app
- For the salary prediction, we used XGBoost for regression after testing different algorithms such as Decision Tree, Random Forest, and K-Neighbors Regressor
- For the country prediction, we used XGBoost for classification after testing different algorithms such as Decision Tree, Random Forest, and K-Neighbors Classifier

Robot image See project

Skills

Experience

Grupo Jurad

Testing Analyst | October 2024 - Currently

• Active involvement in Scrum-based agile teams, participating in sprint planning and review sessions while collaborating to create test cases based on user stories for evaluating new projects or functionalities
• Management and documentation of test cases in JIRA as part of the agile process, assessing improvements to existing services through functional and regression testing
• Testing of REST APIs using Postman and Swagger, validating responses and performing integration tests with SQL Server and PostgreSQL databases

Bodega del cemento

External auditor | October 2023 - July 2024

• Reduced the margin of discrepancies between recorded and actual inventory by 80% by identifying errors in the process and reporting on areas for improvement
• Developed proposals in collaboration with the tax auditor based on identified errors, followed by periodic audits to evaluate compliance

Sheraton Bogotá hotel

Marketing Assistant | July 2021 - June 2022

• Achieved 100% booking capacity for Christmas dinner reservations through pre-event advertising
• Managed Marriott's customer databases alongside the Revenue Manager for subsequent follow-up with account managers
• Developed a mass email campaign in Mailchimp in collaboration with the team to recover 80% of the corporate client base from the three years prior to the pandemic

Contact

I am available to collaborate on new projects! You can contact me via: