Jorge Nacer

I help data-driven companies turn ML models into reliable, production-grade systems that deliver measurable business outcomes, not just notebooks that sit on a shelf.

6+ years as a Data Scientist and ML Engineer, with a 5-year Software Engineering foundation that means I ship end-to-end: from exploratory analysis and model development through containerized deployment, monitoring, and SLO-driven data quality.

What I typically deliver: customer churn and lifetime value models (LightGBM), automated batch prediction pipelines on GCP Vertex AI, multi-container Docker/Kubernetes MLOps workflows, A/B testing frameworks with causal inference, and anomaly detection systems for energy and retail analytics.

What sets me apart: I've owned the full ML lifecycle at enterprise scale (Walmart), optimizing loyalty program budgets through CLV models while maintaining 99.9% data quality SLOs across production dashboards. I don't hand off to engineering; I am the engineer.

Stack: Python, PyTorch, LightGBM, scikit-learn, Docker, Kubernetes, GCP (Vertex AI, BigQuery), AWS, Terraform, FastAPI, Spark, dbt.