I turn data into structured analysis that supports decisions. My portfolio focuses on data quality, analytical validation, forecasting, machine learning, and reproducible data workflows using Python, SQL and BI-oriented tools.
Analytics & BI: SQL · Power BI · Tableau · Excel · KPI analysis · Data visualization
Data: Python · Pandas · NumPy · Cleaning · Transformation · Validation · Reconciliation
Machine Learning: Scikit-learn · NLP · Time Series · Forecasting · Classification
Technical: Git · GitHub · REST APIs · MySQL · MongoDB · AWS S3 · IAM · Linux
A functional MVP that treats catalog reconciliation as a complete data-quality workflow rather than a simple file comparison.
It includes ingestion, profiling, normalization, exact/fuzzy matching, validation rules, exception management, reconciliation outputs, SQLite audit data, Excel/CSV reporting and a Streamlit review dashboard.
Skills demonstrated: Python · Pandas · SQL · Data Quality · Matching · Validation · Reconciliation · Reporting
Exploratory analysis and forecasting of violent-death incident counts in Ecuador using records from 2015–2024. The project covers data cleaning, temporal aggregation, geographic analysis, seasonality, model training and quantitative evaluation.
The public repository excludes the granular raw dataset and focuses on aggregate analysis and forecasting.
Methods: SARIMA/SARIMAX · Random Forest · Gradient Boosting · XGBoost · LSTM · AutoARIMA · Prophet
Evaluation: MAE · MSE · RMSE
Research project applying Natural Language Processing and Machine Learning to automatic hate-speech detection. It demonstrates text processing, feature representation, classification workflows and model evaluation.
Skills demonstrated: Python · NLP · Machine Learning · Text Classification · Research
🔗 View code and project documentation
Data-analysis project using R to explore highway accident information through a reproducible analytical structure with source code, data documentation and project outputs.
Skills demonstrated: R · Data Analysis · Data Visualization · Reproducible Analysis
- Explore and validate data to answer concrete questions.
- Translate data-quality problems into explicit validation and reconciliation rules.
- Structure analytical outputs so findings can be reviewed and communicated.
- Work with SQL, Python, Power BI, Tableau and Excel.
- Use AI tools to accelerate analysis, documentation and development while keeping results reviewable.
- Build reproducible workflows instead of one-off manual analyses.
My background includes work in Artificial Intelligence, Machine Learning and computational methods, including a 2024 Springer publication related to hate-speech detection.
I am currently strengthening the connection between business questions → data exploration → validation → metrics → insights → decisions.
💼 LinkedIn: linkedin.com/in/jairoquelal
💻 GitHub: github.com/jairoequelal-ctrl
📧 Email: jairoequelal@gmail.com
⭐ Open to remote opportunities in Business Analysis, Data Analytics, BI and Analytics Engineering.