I am an engineer focused on bridging the gap between Data Science and Software Engineering. While many data scientists stop at the Jupyter Notebook, I specialize in taking models and data insights and turning them into deployable, scalable web applications.
With a background in Engineering (FUTA), I bring analytical rigor to software development, ensuring that the solutions I build are not just functional, but efficient and production-ready.
If you hire me or collaborate with me, here is the concrete value I bring to your team:
I don't just train models; I serve them.
- Model Deployment: Wrapping ML models in FastAPI endpoints for real-time inference.
- Cloud Architecture: Deploying live production applications to cloud platforms like Render.
- Environment Management: Managing dependencies and runtimes to ensure reproducible code execution.
I build interfaces that make data accessible to stakeholders.
- Backend: Designing asynchronous REST APIs with Python and FastAPI.
- Frontend: Rapidly prototyping interactive dashboards and user interfaces using Streamlit.
- Database: Managing relational data with PostgreSQL and SQL for robust data storage.
- Actionable Insights: Using Pandas and NumPy to clean complex datasets and extract business value.
- Automation: Writing Python scripts to automate repetitive data scraping and reporting tasks.
A Full-Stack Media Sharing Platform I recently engineered a complete social media architecture from scratch to demonstrate full-stack engineering capabilities.
- Tech Stack: FastAPI (Async), Streamlit, PostgreSQL, ImageKit, Render.
- Architecture: Decoupled frontend/backend with RESTful APIs.
- Status: Live Production Deployment.
👉 View Live App | View Source Code
Open for roles in: Machine Learning Engineering, Data Science, and Python Developer.