About the project (description, duration, stage)

Todos los candidatos deben asegurarse de leer atentamente la siguiente descripción del puesto y la información antes de enviar su solicitud.

Hands-on Data Science Lead on a new engagement with a regulated UK & Ireland credit and lending company. The client has consolidated data from multiple business entities into a newly centralized, anonymized data lake and wants to turn it into validated risk analytics — delinquency, probability of default, credit-policy insight — plus an executive-facing natural-language insight layer.

This is a foundational data-science build, not an agentic-AI project. The early work is unglamorous and hands-on: validating data nobody can yet vouch for, then building defensible models on top. You are the senior data scientist the client is missing — you do the work and own the methodology, while leading a small pod and acting as the human-in-the-loop the client explicitly asked for.

Stage: pre-contract / scoping (Phase 1 = current-state assessment + data validation). Duration: multi-phase,



multi-quarter ambition with strong extension probability.

Reporting: Engagement lead / CTO (@Alex Honchar); leads the pod's Data Engineer(s) and the client's offshore data team.

Full-time engagement is preferable.

What you'll actually do (example tasks)
- Profile the anonymized lake hands-on — interrogate tens-of-millions-of-row tables and reproduce and validate the team's existing descriptive statistics, so every number is traceable to source (the client cannot currently answer “how do you know that's correct?”).
- Build and validate the core risk models yourself: PD, delinquency / roll-rate, early-warning, segmentation and scorecards (WOE / IV, logistic regression, gradient boosting).
- Stand up the model-validation discipline that makes outputs audit-defensible: train / test / out-of-time splits, Gini / AUC / KS, calibration, stability (PSI), backtesting and full model documentation.
- Define feature

📌 Data Science Lead (Valencia)
🏢 Neurons Lab
📍 Valencia