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Azul Cruz

@azulcruz

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Data Scientist with 3+ years in predictive modeling, time series, and optimization for environmental decisions.

Colombia

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What I'm looking for

I’m looking to build data-driven predictive and optimization models that turn complex environmental/energy systems into actionable insights, improving decision-making efficiency—ideally in collaborative remote settings during CST business hours.

I’m a Data Scientist with 3+ years of experience in predictive modeling, time series analysis, and optimization frameworks. I translate complex environmental and energy systems into statistical and machine learning models, focusing on turning uncertainty into probabilistic, decision-ready forecasts. I’m strong in Python and SQL, and I build with transparency and reproducibility in mind.

In my current role, I developed and validated an MLP neural network to forecast reservoir inflows and implemented a budget/framework optimization using multidimensional clustering to define operational rules under different scenarios. I’ve also engineered Google Earth Engine pipelines for Sentinel satellite imagery to support deforestation classification and built time-series models to estimate future precipitation regimes. Most recently, as a visiting researcher, I configured and executed General Circulation Models on HPC Linux clusters, working independently across distributed, large-scale experiments.

Experience

Work history, roles, and key accomplishments

Current

Data Science Researcher

Current

Faculty of Environmental and Rural Studies

Jun 2023 - Present (3 years)

Developed and validated an MLP neural network to forecast reservoir inflows from historical inputs, and produced probabilistic forecasts via statistical downscaling of CMIP6 climate scenarios. Built a budget/resource optimization framework using multidimensional clustering and documented methods for reproducible validation.

Python scikit learn Time Series Analysis Multi Layer Perceptrons (MLP)Clustering Model Validation

Visiting Researcher

Okinawa Institute of Science and Technology

Dec 2025 - Apr 2026 (4 months)

Configured and executed General Circulation Models on HPC Linux clusters, managing large-scale data manipulation and experiment tracking. Analyzed extreme weather event ensembles (hurricane genesis, trajectory, and intensity) using modeled and observational datasets while delivering results in a distributed research environment.

General Circulation Models (GCMs)Data Manipulation Observation Model Integration Independent Execution Linux Workflow HPC

Research Associate

Faculty of Environmental and Rural Studies

Jun 2024 - Aug 2025 (1 year 2 months)

Built automated Google Earth Engine pipelines to process Sentinel imagery and perform deforestation binary classification across Colombia (1980–2022). Developed an MLP-based time-series model to forecast precipitation regimes (2022–2050) and translated results into stakeholder-ready insights for agricultural planning.

Google Earth Engine Time Series Multi Layer Perceptrons (MLP)Geospatial analysis Forecasting Interdisciplinary Collaboration

Technical Intern

Brigard Urrutia

Jan 2023 - Aug 2023 (7 months)

Maintained, organized, and performed QA/QC on large climate datasets for client-oriented projects. Developed predictive precipitation modeling to support agricultural planning and produced runoff impact risk assessments for non-technical stakeholders.

predictive modeling Risk Assessment Python SQL Client Facing Analytics