I am a Data Scientist focused on building reproducible, decision-oriented data products. My work spans the entire lifecycle—from raw data preparation and rigorous statistical analysis to ML/DL modeling, NLP applications, and Data Engineering.
My foundation is a unique blend of:
- Analytical & Human Systems: B.Sc. in Physical Therapy and Rehabilitation, providing a deep understanding of complex biological systems, clinical data, and human-centered analysis.
- Core Computing: Degree in Computer Programming, establishing a strong technical base in software logic, algorithm development, and database management.
- Interdisciplinary Data Strategy: Leveraging a clinical background with technical programming skills to engineer data solutions that are both technically robust and practically impactful.
- End-to-End Pipelines: EDA → Feature Engineering → Modeling → Evaluation → Deployment.
- Advanced Modeling: Supervised/Unsupervised Learning, Neural Networks, and Model Interpretability.
- Data Engineering: Designing scalable ETL processes and optimizing data structures for high-load environments.
- Applied AI: NLP and predictive analytics for decision support systems.
| Category | Tools & Competencies |
|---|---|
| Data Science | Python (Pandas, NumPy, Scikit-Learn), SQL, Statistical Experiment Design |
| Machine Learning | Regression, Classification, Clustering, Hyperparameter Optimization |
| Deep Learning & AI | Neural Networks (CNN/RNN), NLP, Prompt Engineering |
| Engineering | Data Quality, Reproducible Pipelines, Database Management |
- 🏗️ Currently focusing on scalable AI-driven infrastructures and axonodeai.
- 🧪 Actively exploring advanced Deep Learning patterns and Data Engineering workflows.
- 🤝 Open for collaboration on Data Science, ML/DL, and Data Engineering projects.
"Engineering intelligence from data to drive the future."