Data Analyst | Python • SQL • Power BI | Machine Learning, Automation & AI
Financial Engineer (ITESO) working as a Process Engineer (Data Analyst) at Ryder, on the logistics implementation of HP's new distribution centers in the US. I turn operational and financial data into Power BI reports, Python models and automations that save real hours.
- Built a Power BI report that consolidates 6 tracking sources into a star schema refreshed 5 times a day, giving project leads and PMs visibility of status and blockers.
- Automated a backlog report for 22 HP customers with Power Automate and Office Scripts, removing ~3 hours of manual work per week.
- Test end-to-end logistics scenarios in SAP S/4HANA, TestRail and SEEBURGER (B2B/EDI).
Work code is confidential, so the repositories below are academic and personal projects.
| Project | What it does | Highlights |
|---|---|---|
| Sector Rotation Strategy (ML) | Classifies economic-cycle phases from four leading indicators to rotate sectors | MLP (scikit-learn): 88% accuracy, weighted F1 0.88; backtested against the S&P 500 |
| Asset Allocation Backtesting | Streamlit dashboard that backtests quantitative portfolio strategies | 11 strategies, 3 optimizers (SLSQP, Monte Carlo with Optuna, COBYLA), coded from scratch |
| Credit Approval Model | Predicts credit application approval from four applicant financial variables | Logistic regression: ROC AUC 0.78 on ~18k hold-out applications; benchmarked against random forest, XGBoost and a neural network |
| Data Coding Challenges | Documented HackerRank solutions | 31 T-SQL and 7 Python problems, each with a summary and approach |
- Python: pandas, NumPy, scikit-learn, XGBoost, statsmodels, matplotlib, seaborn, Streamlit, Optuna
- SQL: T-SQL, DuckDB
- BI & automation: Power BI (DAX, Power Query), Power Automate, Office Scripts, Excel
- Tools: Git, GitHub, SAP S/4HANA, TestRail
- Microsoft Certified: Power BI Data Analyst Associate (PL-300), 2026
- HackerRank SQL (Advanced)