I'm a Data Scientist with a passion for building smart, scalable, and user-friendly systems. I come from a background in business operations and customer experience, and I've recently transitioned into data science to combine my business knowledge with data-driven impact.
I'm deeply curious about all things data and programming, from analytics to MLOps, from classical ML to modern LLMs. I'm especially interested in:
- Operationalising machine learning
- LLM fine-tuning and post-training techniques
- Backend-first, full-stack development for data products
- Mobile app development
I'm focused on expanding my skills in:
- App Development (Flutter and Dart)
- MLOps (deployment, monitoring, reproducibility)
- LLM post-training techniques (e.g. RAG, LoRA, fine-tuning)
- Backend development (Python, Go, APIs, and systems design)
I'm open to collaborating on machine learning and backend-focused projects — especially those with a real-world impact or open-source potential. If you're working on something exciting in the data, ML, or tools-for-developers space, let’s connect.
- Languages & Frameworks: Python, SQL, Dart/Flutter (learning)
- Data & ML: Polars, pandas, Scikit-learn, PyTorch, Tableau, Marimo, HuggingFace, PyMC
- Dev & Ops: uv, GitHub, VS Code, Docker, n8n, FastAPI, Django, Flask
I've spent over a decade in the retail and ecommerce industry, leading operations, digital strategy, and customer support teams. In 2025, I officially stepped into a data science role and have been driving insights, automation, and tooling. I'm motivated by building backend systems that are efficient, elegant, and genuinely helpful.