Tools & technologies
Tabular data modelling
Most business problems are tabular data.
Most business problems are tabular data. Solid models to predict default, churn, demand or risk, with the evaluation a real decision needs.
Calibration, not just ranking
If you are going to make decisions with the probability, it has to be reliable. I calibrate the model and check it with the Brier score and the reliability curve, so that a 0.7 really means 70%.
The threshold matters more than the model
I pick the decision threshold that minimises the real business cost, not the default 0.5. That often changes the outcome more than changing the model.
Operating locations
Studio in Madrid
Based in Madrid, working remotely with brands, studios and agencies inside and outside Spain.
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Decision flow
Calibrated probabilities.
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Friction map
Cost-based threshold.
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Journey shape
Error analysis.
Work with JMWEB
Let's build something that reaches production.
It all starts with a conversation. Bring a dataset, a goal or a model that is stuck; I will take care of the rest.
Start a project
Next projects:

Credit Risk Platform
End-to-end MLOps platform for credit-default scoring: reproducible training with a versioned model registry, a FastAPI inference API with input validation, PSI drift monitoring and a Prometheus and Grafana observability stack, all containerised with CI. Code at github.com/delcenjo/credit-risk-platform.
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Transformer from scratch
A GPT-style language model implemented from scratch in PyTorch: multi-head attention, causal masking and residual blocks written by hand, plus a byte-pair tokenizer and an ablation study. Code at github.com/delcenjo/transformer-from-scratch.
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Credit Risk Model
Credit-default risk model with rigorous evaluation: a leakage-free pipeline, cross-validated model comparison, calibrated probabilities, a cost-based decision threshold and per-segment error analysis. Code at github.com/delcenjo/credit-risk.
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AI Insight Assistant
An assistant that combines RAG and a SQL agent over your data: it retrieves from a document corpus and queries a database, served with FastAPI and Streamlit and packaged in Docker. Code at github.com/delcenjo/ai-insight-assistant.
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