o Led an independent data-intensive project within an international laboratory, self-directing workflow and deliverables in a fast-paced global environment, demonstrated constant adaptability by rapidly integrating new computational methodologies and experimental data pipelines across rotating project priorities. o Managed and analyzed large biological datasets from primary screening assays in a global research environment. o Built and curated structured analytical datasets from large-scale experimental screening assays, enabling data-driven compound prioritization within a cross-functional international research team. o Participated in cross-functional scientific discussions and collaborative research planning with international teams.

o Manager of the Communications Committee of Latin American Society for TB and other Mycobacteriosis (SLAMTB) — leading regional scientific society in the field. o Coordination activities at SLAMTB international meetings in Colombia (2023) and Uruguay (2025). o Contributed to dissemination strategy, social network activities and outreach activities.

o Led research project within a 20-person group embedded in a 200-person multidisciplinary institution, coordinated collaborative projects with international partners in the United States, Uruguay, France, and multiple Argentine research institutions. o Project Lead (2023-2025) — ML Prediction for Product Candidate Prioritization (GitHub): Led end-to-end design and delivery of an ML pipeline to classify and rank 50,000+ compounds from high-throughput screening assays. Stack: XGBoost, RDKit, SHAP, Bayesian optimization, Streamlit. o Project Lead (2024-2026) —Patient Treatment Churn Prediction (GitHub): Designed an ML pipeline to predict treatment dropout at enrollment using 29 variables, applied economic cost-model threshold optimization and LIME explainability. Stack: Python, scikit-learn, LIME, Power BI. o Performed systematic data mining across complex databases, built structured analytical datasets for target identification of best strategy. o Data Analysis and Visualization for conferences and weekly meetings, data driven decision explanation. o Communicated analytical findings and research strategies to multidisciplinary stakeholders at 9+ international scientific conferences. o Co-supervised an undergraduate thesis on large-scale inhibitor discovery, defined workflow, milestones, and co-presented results. Team coordination and problem solving for group objectives. o 6+ years of domain expertise in drug discovery, high-throughput screening, and infection models. o Organized and chaired AI and informatics seminars for the institution, curating content on emerging machine learning methods, statistical modeling tools, and computational biology approaches. o Completed advanced doctoral formation in Digital Image Analysis and Advanced Informatics Tools.