PhD-educated Data Scientist with 5+ years of research experience applying machine learning, statistical analysis, and Python to extract insights from complex datasets, primarily high-dimensional human motion data. Proven expertise in the end-to-end data science lifecycle: from data acquisition (motion capture, VR) and curation to feature engineering, dimensionality reduction, unsupervised (clustering) and supervised (classification) model development, and evaluation using Python (Scikit-learn, Pandas, NumPy). Seeking to leverage advanced analytical and ML skills to solve challenging business problems and drive data-informed decisions in a Data Science, ML, or Analytics role.
Doctor of Philosophy in Mechanical Engineering, 2021
The University of Sheffield
Master of Engineering, 2011
Universidad La Salle Bajio
BEng in Mechanical and Electrical Engineering, 2009
Universidad La Salle Bajio
Python (Expert: Pandas, NumPy, Scikit-learn, Matplotlib), SQL, MATLAB, Version Control (Git, GitHub, GitLab, Bitbucket)
Algorithms: Unsupervised Clustering (K-Means, Hierarchical, Density-based), Supervised Classification (Decision Trees, Random Forest), Regression, Bayesian Methods. Techniques: Feature Engineering, Dimensionality Reduction (e.g., PCA, T-SNE, UMAP), Model Training & Evaluation, Statistical Analysis, Time Series Analysis.
Scikit-learn, Pandas, NumPy, Matplotlib, Pytorch
Marker-based (e.g., Vicon Motion Systems, CODA motion), and marker-less (Openpose, DeepLabCut, OpenCV), Action Classification, Motion Modelling
Unity, HTC Vive, Oculus Quest
Spanish (Native), English, German (Basic-Intermediate)
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