My Projects
Hello! Glad to see you here. This is a collection of my data science and ML projects.
Hello! Glad to see you here. This is a collection of my data science and ML projects.
I am a Canadian software janitor turned data scientist and engineer. I graduated from Queen's University in 2018 with a Bachelor of Computing and specialization in Software Design. In the last 4 years I have worked on multinational software development projects for RWE, IAG, and FPT Software.
Besides technology, I also like to swim, to streeetch, and to debate philosophy and the global state of affairs with my friends.
I have been to 27 countries and lived in Guyana, Canada, Ghana, Malawi, Tanzania, Vietnam, and Thailand.
In 2025 I am looking for remote working opportunities and focusing my efforts on Web3 technologies.
During my four-year tenure at this leading IT consulting firm, I worked in various roles—from Software Engineer to Data Engineer and eventually Data Analyst. My primary focus was to help FPT Software win and deliver successful projects for international clients. Throughout this period, I developed scalable data pipelines, created interactive dashboards for performance insights, and ensured data quality standards across multiple projects.
From 2020 to 2023, I consulted for RWE, a major German energy company. My main achievement was building an administrative web application using Python and Django, which I deployed via Azure DevOps in a containerized (Docker) environment. I also maintained RESTful APIs for real-time data sharing with other applications in the RWE ecosystem and setup a Celery messaging service to achieve synchronicity with legacy databases.
In the latter half of 2023, I transitioned to a Data Engineer role for IAG, focusing on migrating their on-premise Greenplum databases to Google Cloud Platform using dbt. I developed modular, automated pipelines with Apache Airflow, implemented monitoring and alert systems, and enforced strict data quality checks. In 2024, I evolved into an analytical role, leveraging these pipelines to generate performance metrics and drive data-driven decision-making for the organization.
