Francisco Javier Ordoñez Araujo JavierOrdonezA

Hi 👋, I'm F. Javier Ordoñez A

Programming Languages and OS: Python, SQL, C++, LaTeX, Octave/MATLAB, Linux, Git
Data Analysis: Pandas, Numpy, Excel, Seaborn, Scipy, Tableau, PowerBI
Machine Learning: Scikit-Learn, PyTorch, TensorFlow, OpenCV, Scikit-image
Cloud Computing: Cloud Computing, Azure(Databricks), Colab
Other: Jupyter NoteBook, VS Code, LATEX, MS Excel, Microsoft Office, VBA
Technical: Regression/Classification (GLM, Logistic, KNN, CART), Clustering (K-Means, DBSCAN, Decision Tree Model), Dimensionality Reduction (PCA, LDA), Deep Learning (CNN), Analytical Statistics (hypothesis testing, A/B testing)
Soft Skills: Leadership, Teamwork, Organization, Efficiency, Dedicated, Inclusive, Collaboration.

IBM Data Science Professional Certificate, Completed a comprehensive program covering Data Science methodologies, Python, SQL, Data Visualization, Machine Learning, and Cloud-based capstone projects.
Postgraduate: Master’s Degree in Science - Astronomy, National University of Colombia, Bogotá D.C., Colombia (2022-2024) - GPA: 4.7/5.0, Honors: Meritorious thesis.
Undergraduate: Bachelor’s Degree in Physics, National University of Colombia, Bogotá D.C., Colombia (2016-2021) - GPA: 4.2/5.0.
Courses:
- Deep Learning Computer Vision, NMA Neuromatch Academy
- The Structured Query Language (SQL), University of Colorado Boulder, Online, (2023-2023) - GPA: 92/100.
- Advanced Excel Specialization, University of Colorado Boulder, Online, (2024-2024) - GPA: 98/100.
- Complete Git Specialization, LearnKartS, Online, (2024-2024) - GPA: 95/100.

Junior Data Scientist, Lilianurse, Bogotá D.C., Colombia (2023): I contributed to developing and implementing a decision tree model to predict sales trends and target loyal customers. I provided technical support in data interpretation and advanced data analysis to optimize sales strategies.
Teaching Assistant Fellow, National University of Colombia, Bogotá D.C., Colombia (2022-2023): I tutored master’s students in Astrophysics, focusing on helping them solve programming challenges and implementing machine-learning techniques to analyze astronomical data. In this role, I sharpened my soft skills, worked effectively in a team, and conveyed complex ideas in a simple and accessible manner.

KU Leuven Faculty of Science, Leuven, Belgium (2024): I focused on integrating data analysis of observations from various AIA filters to understand better cold events observed with ALMA band 3. Also, I utilized Convolutional Neural Networks (CNN) to analyze solar observations and detect and study cold events in the sun.

Rosseland Center for Solar Physics (RoCS), Oslo, Norway (2023): I developed a Python method for aligning images using the Pearson coefficient available here, on my GitHub. I also gained expertise in clustering methods like K-Means and DBSCAN. I performed advanced time series analysis using FFT and Wavelet Transform to study variable correlations, enhancing my data analysis, control version (Git), and algorithm development skills.

"Data and Image Analysis: Comparative Image Alignment for Multiple Telescopes: ALMA, IRIS, SDO", eSPECTRA, Vol. 2, 2024, doi: https://arxiv.org/abs/2404.04401.
"Data Analysis and Dynamics Study: the cold solar chromosphere dynamics observed with ALMA", UNAL Master Thesis repository, doi: https://repositorio.unal.edu.co/handle/unal/85838.
"Data Analysis: Study of Correlations between Variables in Sunspots", Ciencia en Desarrollo, Vol 1, 2022, doi: https://doi.org/10.19053/01217488.v1.n2E.2022.15245.