CHEBELYON(1) Career Manual CHEBELYON(1)
NAME
eddy_chebelyon — AI engineer, ML engineer, data scientist, economist
SYNOPSIS
eddy [--python | --sql | --aws | --terraform] [--coffee] <dataset>
DESCRIPTION
Self-taught, results-driven AI Engineer with 5+ years of experience in data science, machine learning, infrastructure deployment, and geospatial analytics. Motivated by novel problems and opportunities to creatively solve complex technical challenges. Previous professional life as research economist and international development project manager.
| Category | Packages |
|---|---|
| Languages | Python, SQL, R, JavaScript |
| AI/ML | Scikit-learn, TensorFlow, PyTorch, MLflow |
| Cloud | AWS, GCP |
| Data Eng | Apache Spark, Airflow, Kafka, Docker, Kubernetes |
| Databases | PostgreSQL, MongoDB, Redis, Elasticsearch |
| Geospatial | PostGIS, GDAL, GeoPandas, Geoserver, QGIS, Rasterio |
| IaC/MLOps | OpenTofu, Terragrunt, CI/CD, GitHub Actions, Model versioning |
| API | FastAPI |
| Statistics | Econometrics, Causal Inference, Time Series, Panel Data |
- Design and implement end-to-end AI solutions for production environments
- Lead development of ML model serving infrastructure and real-time inference systems
- Collaborate with product teams to integrate AI capabilities into customer-facing applications
- Optimize model performance and scalability for high-throughput production workloads
- Mentor junior engineers and establish best practices for AI development lifecycle
- Built and maintained scalable data pipelines processing geospatial data from multiple sources into machine learning systems
- Developed machine learning infrastructure supporting predictive models for population estimation and socioeconomic indicators
- Automated data flow processes, reducing manual intervention and improving data quality
- Specialized in cloud computing and data engineering solutions for geospatial analytics
- Conducted advanced data analysis for Mobile Salaries Payments project in Afghanistan
- Engaged with policy makers on project implementation and provided data-driven recommendations
- Developed statistical models to evaluate program effectiveness and impact
- Managed complex datasets and performed econometric analysis for policy research
- Taught graduate-level courses in Quantitative Methods (regression analysis, panel data, time series, causal inference)
- Conducted research on climate economics, quantifying temperature effects on economic output
- Mentored students in statistical analysis and econometric modeling techniques
- Managed large-scale field data collection operations across Northern Kenya and Southern Ethiopia
- Implemented machine learning solutions for crowd-sourced rangeland condition monitoring (Cornell University collaboration)
- Developed data collection protocols and quality assurance processes for international research projects
- Led cross-cultural teams and coordinated with international stakeholders
Cloud-native ML pipeline processing satellite imagery and demographic data. Substantial reduction in processing time through optimized infrastructure scaling. Integrated satellite imagery, census data, and survey responses.
Conversational AI agent enabling customers to query complex datasets through natural language. RAG architecture combining LLMs with domain-specific knowledge base. High user satisfaction, reduced analyst support queries.
High-performance tile server serving web maps to client-facing applications using GeoServer, PostgreSQL, and FastAPI. Significantly reduced map rendering times.
Econometric models quantifying temperature effects on economic output (PI: Kate Ricke). Panel data analysis and causal inference. Published in peer-reviewed academic journals.
Development Economics, Econometrics, International Development. Quantitative methods, economic policy analysis, Spanish language studies.
Microeconomics and Development Economics. Thesis on household labor allocation for smallholder rural farmers.
Wildlife Management. Environmental science, resource conservation, and ecosystem management.