Tools & technologies
ML consulting and audit
Have a model that is not quite working, or a team that wants to start right? I review data, methodology and deployment, and tell you what to fix, no hype.
Have a model that is not quite working, or a team that wants to start right? I review data, methodology and deployment, and tell you what to fix, no hype.
Where it actually breaks
Most models do not fail because of the algorithm, but because of data leakage, a badly chosen metric or an optimistic evaluation. I look for that first.
Judgement, not hype
Sometimes the answer is a simpler model, sometimes it is that you do not need an LLM. I tell you what actually moves the needle for your case.
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
No hype.
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Friction map
Leakage first.
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Journey shape
The simple model usually wins.
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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