Data Scientist with a Bachelor’s degree in Statistics and Information Management.
I bridge the gap between rigorous statistical methodology and cutting-edge AI. My goal is to build intelligent systems that are not just high-performing, but also transparent, explainable, and grounded in solid data principles.
- AI Agents: Developing autonomous agents capable of complex task execution and multi-step reasoning.
- RAG Systems: Implementing Retrieval-Augmented Generation pipelines to connect LLMs with private, dynamic knowledge bases.
- ML & Fine-Tuning: Training and optimizing supervised models and LLMs for domain-specific applications.
- Explainability (XAI): Applying statistical rigor to ensure "black box" models remain interpretable and trustworthy.
- Machine Learning Operations: Model fine-tuning, evaluation, and deployment.
- Statistical Foundations: Multivariate analysis and dimensionality reduction (SVD, PCA, SOM).
- Modern AI Stack: Transformer architectures, LangFlow orchestration, and Vector Databases.
Languages & Core:
AI Frameworks & Tools:
I’m open to exciting projects involving AI Agents, RAG pipelines, and ML optimization. If you need a Data Scientist who understands both the math and the code, let’s connect!