Santiago Infante

I’m a Chemistry graduate building end-to-end data pipelines and AI-driven research workflows. In my current role as a Computational Chemist – AI/ML Researcher, I focus on turning molecular datasets into reliable predictions and actionable research outputs.

I’ve processed 100k+ molecular records from ChEMBL and GPCRdb using Python with RDKit and OpenBabel, including data cleaning and validation with pandas and NumPy. I also train and evaluate models such as a Random Forest classifier and a D-MPNN for pharmacological potency regression, delivering results on held-out test sets.

Beyond classical ML, I’ve applied deep learning for de novo molecular generation with Reinvent4, evaluating outputs using chem-informatics metrics and domain knowledge. I’ve also conducted molecular dynamics simulations (GROMACS) and analyzed trajectory data programmatically with Python.

I bring strong documentation and communication skills in English and Spanish, producing technical reports and presenting findings to faculty and research peers. I’m now seeking an entry-level Data Analyst or AI opportunity where analytical rigor and ML skills create real impact, and where I can contribute to AI evaluation and RLHF data annotation.