Experience
A timeline of my professional journey and key achievements.
Data & AI Engineer (Consultant), Computational Biology Data Insights & Management
Roche
Engineered advanced GenAI systems and built scalable AI-driven data applications for analyzing immunological sequencing data.
Key Achievements
- Engineered advanced GenAI systems leveraging LangGraph for complex multi-agent workflows, significantly enhancing research productivity
- Built a scalable AI-driven data application on AWS to integrate and analyze immunological sequencing data, improving data accessibility and interpretation
- Designed automated ETL pipelines for high-volume biological datasets, optimizing analytical efficiency and data accessibility
- Implemented an LLM-based conversational interface enabling researchers to query large immunological databases via natural language (text-to-SQL), dramatically reducing analysis from hours to minutes
Research Intern, Medical Affairs, Primary Care - Vaccines
Pfizer
Developed ETL pipelines for epidemiological data analysis, conducted comparative studies on vaccines, and supported Lyme disease research.
Key Achievements
- Built ETL pipelines to process epidemiological datasets (ABCs, NML), enabling real-time analysis of Invasive Pneumococcal Disease (IPD) trends
- Led comparative analytics on IPD serotype coverage across Pfizer and competitor vaccines, delivering insights for market positioning
- Supported data-driven modeling to reveal 5-11x underreporting of Lyme disease in Manitoba, informing vaccine trial design and public health planning
Research Assistant I, Biofluids and Global Health Lab
Department of Bioengineering, McGill University
Optimized a 3D phage-bacteria simulation model using parallel programming to improve performance and scalability for high-dimensional biological data.
Graduate Researcher, Biofluids and Global Health Lab
McGill University
Developed Bayesian machine learning pipelines for calibrating COVID-19 transmission models and evaluating public health interventions in Quebec.
Key Achievements
- Developed a Bayesian machine learning pipeline (ABC-SMC) to calibrate a COVID-19 transmission model for evaluating public health interventions
- Simulated counterfactual vaccination scenarios to assess the epidemiological impact of hesitancy and age-prioritized strategies
- Demonstrated that government interventions were near-optimal and identified a potential 2% hospitalization reduction through targeted refinements
Teaching Assistant, Introduction to Physical, Molecular and Cellular Biology
McGill University
Led computational biology labs, guiding students in applying data analysis methods to molecular transport and cell physiology.
Research Assistant, Epiverse TRACE
Faculty of Medicine, Universidad de los Andes
Developed data packages for Aedes-borne disease transmission analysis and implemented web-scraping pipelines for data integration.
Key Achievements
- Developed data packages to enhance mathematical and statistical tools for understanding Aedes-borne disease transmission
- Conducted data audit and curation of vector-borne disease databases by reviewing health, demographic, and socioeconomic datasets
- Implemented web-scraping pipelines to retrieve and standardize government data, integrating it with local datasets
Undergraduate Researcher, BIOMAC and COLEV labs
Department of Biomedical Engineering, Universidad de los Andes
Designed models for school reopening evaluation and developed COVID-19 forecasting tools to inform public health decisions.
Key Achievements
- Designed models showing partial school reopening (up to 55%) was feasible without raising mortality under strict quarantine
- Engineered predictive tools using statistical, ML, and deep learning models to forecast COVID-19 spread in Colombia
- Built back-end systems for web applications using mathematical models to inform the public about COVID-19 risks
Undergraduate Researcher, Bionanotechnology and Biomaterials Lab
Universidad de los Andes
Coded multiphase flow models to simulate nanofluids behavior in microfluidic devices to propose pharmaceutical transport systems.
Intern, Neuromodulation Business Unit
Boston Scientific
Oversaw machine learning analysis (XGBoost) to assess the cost-effectiveness of deep brain and spinal cord stimulation therapies.