Isabel Domínguez Jiménez

Profile

I am a Data Scientist and Physicist with more than 12 years of experience in research, teaching, and computational modeling. I combine scientific rigor with machine learning and data analytics to build predictive models and data-driven solutions for complex problems.

Technical Skills

• Programming: Python, C++, SQL
• Libraries: Pandas, Scikit-learn, TensorFlow, PyTorch, Seaborn, Matplotlib
• Tools: Jupyter, Streamlit, Tableau, Docker, GitHub, Render
• Languages: Spanish (Native), English (B2)

Experience

Professor & Researcher — Universidad Autónoma de Sinaloa (2013–Present)
Designed and taught 50+ courses in Computational Physics and Data Analysis. Supervised 11 theses integrating Python and machine learning into research workflows.

Visiting Professor — Universidad de Colima (2022–2023)
Applied ML techniques to physical simulations and improved data workflows in research collaborations.

Postdoctoral Researcher — UNAM (2011–2012)
Developed Monte Carlo models and optimized algorithms for high-energy physics data.

Education

• Bootcamp in Data Science – TripleTen (2024)
• PhD in Physics – UNAM (2011)
• Master’s in Physics – CINVESTAV Mérida (2003)
• Bachelor’s in Physics – UAEM (2001)

Featured Projects

Vehicle Price Prediction

Machine learning model to predict vehicle prices based on key features, deployed on Render using Streamlit.

Tech: Python, Scikit-learn, Pandas, Streamlit

Oil Extraction Analysis

Regression and optimization model to forecast oil extraction volumes.

Tech: Scikit-learn, Numpy, GridSearchCV

Movie Review Classification

Sentiment analysis using NLP with TF-IDF, BERT and SpaCy to classify movie reviews.

Tech: Python, NLTK, Transformers, Torch

Age Determination

Computer vision model to predict age from facial images using CNNs.

Tech: TensorFlow, Scikit-learn

Photon Production Simulation

Numerical modeling of photon emission in magnetic-field environments for high-energy physics.

Tech: ROOT (C++), Mathematica

Career Objective

To apply my experience in data science and machine learning to real-world problems, contributing to innovative projects that combine scientific reasoning, AI, and decision-making analytics.