Data Scientist focused on practical ML systems.

I build end-to-end machine learning projects. From data preparation to model training, evaluation, and reporting.

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Projects

All Repos
Phishing Email Detection (NLP)

Built and evaluated an LSTM-based classifier to label emails as phishing vs safe.

Pytorch LSTM NLP
  • Data: ~18k emails (Kaggle)
  • Evaluation: Accuracy, precision/recall, F1
  • Result: 95% accuracy
Code Report Demo

Skills

Modeling
Classification, regression, NLP, evaluation, tuning
Python
pandas, NumPy, scikit-learn, TensorFlow/Keras
Data
SQL, cleaning, feature engineering, validation splits
Communication
Dashboards, writeups, metrics, stakeholder framing

Experience & Education

M.S. Data Analytics — WGU
2026
  • Capstone: phishing email classification using an LSTM with rigorous evaluation artifacts.
  • Emphasis on reproducible workflows, Git-based versioning, and clear reporting.
Certs / Tools
  • Git, GitHub/GitLab
  • Jupyter, PyCharm
  • Tableau

About

I focus on building practical ML solutions with strong evaluation and clear communication. I enjoy NLP problems, end-to-end pipelines, and turning messy datasets into reliable models.

Contact

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