Yamil Padilla – Data | ML | AI Resume

A Technology Leader with experience developing software, managing applications, and leading teams to deliver world-class solutions. Proven success in improving business value, customer experiences, emergency response and functionality for both private and government sectors. Expertise in developing and implementing ML/AI solutions, reporting, data visualizations, modernization, and innovation efforts. Recognized for contributions to high impact projects, including emergency and pandemic response.

Key Accomplishments

  • Assisting Pharmacy chains in identifying key locations to enable testing for 80% of the US population and reducing expenses by 30%.
  • Epidemiological scenario simulations to test the resiliency of the US Strategic National Stockpile supply chain against new pathogens.
  • Deploying Large Language Models on edge devices to allow privacy and security focused exploration of large sensitive documents.
  • Risk modeling of highly complex financial data, allowing for the Administration for Children and Families to have early corrective actions with grant recipients.
  • Developing highly detailed transportation infrastructure recovery visualizations for the Federal Emergency Management Agency and the Department of Transportation, enabling monitoring of the restoration progress.
  • Establishing a technology strategy for the Flight Standards Service, enabling realignment of applications and business functions.
  • Data warehouse implementation for improved analysis and exploration of manufacturing production lines across the globe.

Recent Experience

Consulting Data Scientist, ML and AI Engineer
Self-employed

08-2024 – Present
I develop and deploy automated software on analytics, business intelligence, data pipelines, machine learning and artificial intelligence as well as leveraging data science to solve complex business problems. Whether in the cloud or on-premise, strategic initiatives or implementation, I advise to build business value and drive comprehensive solutions. Always employing the latest technologies and techniques.

Lead Data Scientist and Machine Learning Engineer
Administration for Children and Families

01-2024 – 08-2024
Reported to the Chief Technology Officer, successfully launching two vital data products within the initial 30 days of assuming the role. Directed and coordinated a team of 8 Data Scientists, Engineers, and Analysts to deliver quick turn analytics and data engineering efforts, growing the portfolio over 20 projects in less than 6 months.

Senior Staff Machine Learning Engineer
Johns Hopkins University Applied Physics Laboratory

05-2022 – 01-2024
Developed machine learning models for the Centers of Disease Control and Prevention (CDC) COVID-19 Emergency Response, Administration for Strategic Preparedness and Response (ASPR) and the NAVY Bureau of Medicine and Surgery (BUMED) using supervised/unsupervised algorithms including agent-based simulations, random forests, boosted trees, PCA, K-means clustering, and PyTorch deep learning for classification, prediction, historical analysis and forecasting epidemic outcomes for programs of health management, vaccine/test manufacturing, and distribution.

Senior Data Architect
Executive Softworks

09-2021 – 05-2022
Developed SQL code, views, stored procedures and ELT pipelines on Snowflake for a client Manufacturing Production Analysis Databases migration. This work enabled near-real-time analysis of production lines across all manufacturing centers, saving time from manual querying, enhancing operational insights and decision-making capabilities.

Emergency Response Cadre and Geographic Information Systems Engineer
US Department of Transportation

04-2018 – 09-2021
Supported emergency response and coordination activities for hurricane and wildfire seasons 2018-2021, ensuring quick passage of response personnel, road openings and closures, provision of humanitarian aid and restoration of infrastructure to affected areas.

Senior Advisor on Technology Management and Data Science
Federal Aviation Administration

12-2010 – 09-2021
Most recently formed a new technology strategy and division focused on business systems, DevSecOps, enterprise architecture, innovation and data science, leveraging twelve-factor methodology, Agile practices, and overseeing over 40 personnel across multiple organizations with a budget of over $150M.

Technologies Employed

  • Data and Machine Learning Automation
    • Spark, Airflow, Palantir, Scikit-Learn, XGBoost, PyTorch, Transformers, OpenAI, Meta AI
  • Data Visualizations
    • Tableau, PowerBI, Matplotlib, Plotly, Dash, Streamlit
  • Infrastructure
    • AWS, Sagemaker, Glue, Azure, Azure Machine Learning, Azure Data Factory, Docker, Artifactory, MariaDB, PostgreSQL
  • Code Development
    • Python, R, SQL, Git, Jira, Confluence, GitHub, GitLab, VSCode, Rstudio, Jupyter, Agile, Kanban

Education

BS in Electronics Engineering
University of Puerto Rico, 2008