Developed a Demand forecasting software for TriMark
Feb,2023Part of McDonald's digital transformation. We upgraded their existing UI and database, integrating the latest technological advancements.
March,2022Analyzed McDonald's CCTV data with CVAT for serving time and rush hour insights.
Jan,2022
1. Upgraded McDonald's database from legacy Oracle to PostgreSQL using Liquibase.
2. Deployed local PostgreSQL using Docker for simplified setup and management.
3. Utilized containerization for PostgreSQL to ensure consistency and isolation.
4. Implemented a scheduler task in Spring Boot for database synchronization.
5. Developed APIs for UI tasks using Java Gradle, maintained with Swagger for front-end compatibility.
6. Managed version control by deploying code to Git.
7. Maintained code quality standards using SonarLint.
1. Analyzed data from 12 ERPs, preparing it for demand forecasting.
2. Tested various ML models using Python, accurately predicting sales for 10 weeks.
3. Implemented Airflow DAGs for automating data preprocessing and ML tasks.
4. Orchestrated model scheduling and execution, deploying Airflow locally via Docker.
5. Established a connection between Airflow and an S3 bucket for data management.
6. Maintained a GitHub repository for version control and DAGs documentation.
7. Ensured code quality standards using SonarQube.