16 publicaciones de empleo destacadas de python full stack en madrid, md (¡Están contratando!)

Data Science Lead
Neurons Lab —Madrid, Madrid provincia
- Jornada completa
- Teletrabajo
- SQL
- AWS
- Python
10d
Product Management Intern ES
Lenovo —Madrid, Madrid provincia
- Jornada completa
- Español
- Microsoft Excel
- Inglés
5d
Cybersecurity Engineer for Network Security
Roche —Madrid, Madrid provincia
- Jornada completa
- Grado
- Gestión de conflictos
- Scripting
Cybersecurity Engineer for Internal Network Defense
Roche —Madrid, Madrid provincia
- Jornada completa
- Grado
- Gestión de conflictos
- Scripting
Cybersecurity Engineer for Network Security observability
Roche —Madrid, Madrid provincia
- Jornada completa
- Azure
- Informática
- DevOps
IT Security Engineer (m/f/d)
Deutsche Pfandbriefbank AG —Madrid, Madrid provincia
- Inglés
- Scripting
- Python
Senior Cybersecurity Engineer for Secure Access Network
Roche —Madrid, Madrid provincia
- Jornada completa
- Grado
- Gestión de conflictos
- Scripting
12d
Cybersecurity Engineer for Edge Defense (Cloud)
Roche —Madrid, Madrid provincia
- Jornada completa
- Azure
- AWS
- Grado
13d
Cybersecurity Engineer for Edge Network Security
Roche —Madrid, Madrid provincia
- Jornada completa
- Azure
- AWS
- Grado
Director, Data Engineering (Capital Markets)
JLL —Madrid, Madrid provincia
- Azure
- Informática
- DevOps
Solution Sales Specialist Apps
SoftwareONE —Madrid, Madrid provincia
- Jornada completa
- Trabajo híbrido
- Español
- Inglés
- Java
Lead, Software Engineering
Bain & Company Inc —Lisboa
- Jornada completa
- Máster
Consultor /a Dynatrace
Accenture —Madrid, Madrid provincia
- Jornada completa
- Trabajo híbrido
- Español
- Python
- Reparto de beneficios empresariales
- Seguro médico privado
Senior Data Platform / Data Engineer
Straumann Group —La Moraleja, Madrid provincia
- Jornada completa
- AWS
- Machine learning
- Python
Full Stack Engineer
Amino & 24i —Madrid, Madrid provincia
- Trabajo híbrido
- DevOps
- SQL
- AWS
Solicitud rápida
12h
Senior Fullstack Engineer (Java/kotlin + React)
Parser Limited —Madrid, Madrid provincia
- Jornada completa
- Trabajo híbrido
- Azure
- Informática
- DevOps
Solicitud rápida
12h

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Product Management Intern ES
Lenovo —Madrid, Madrid provincia
We use AI-based tools to support some of our processes (e.g. online interviews recordings and transcripts) in order to achieve better efficiency, accuracy and…
5d
#DISCOVER II 2026-2027 Graduate/Student Airworthiness & Product Integrity Internship
Airbus Defence and Space SAU —Getafe, Madrid provincia
Support digital initiatives and contribute to management an improvement of tools used within the Center of Competences (CoC). Support to Management <JF-FA-ES>.

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Data Science Lead

Neurons Lab
Madrid, Madrid provincia

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Detalles del empleo

Jornada completa
Hace 10 días

Cualificaciones

Data lake
SQL
AWS
Cloud
Python

Descripción completa del empleo

About the project (description, duration, stage)

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 logic with the Data Engineer and write it yourself in SQL / dbt / Python; specify the harmonized definitions the semantic layer must serve.
Prototype and validate the natural-language insight layer (text-to-SQL / RAG over the semantic layer); check answer correctness and add guardrails.
Run a credit-policy / cut-off analysis showing where the client could tighten policy or reduce delinquency — the concrete insight their own clients keep asking for.
Lead a small pod (Data Engineer, client's junior offshore data people): set tasks, review work, be the quality bar and the human-in-the-loop.
Front the client's data leadership: present findings, explain methodology to non-technical executives, and shape the phased roadmap / SoW.

Skills (hands-on first)

Expert Python for data science (pandas / Polars, scikit-learn, statsmodels) and strong SQL over large tables
Credit-risk / financial modeling: scorecards, PD, delinquency, segmentation, model validation and governance
Data validation, profiling and feature engineering on messy enterprise data
dbt / semantic modeling; partnering with data engineering on the harmonization layer
GenAI insight layer: text-to-SQL, RAG over structured data, evaluation and guardrails
Methodology, lineage and documentation that survives audit; able to explain it to executives
Leadership of small delivery pods and distributed / offshore teams

Knowledge

GDPR fundamentals (anonymization vs pseudonymization, UK / EU data residency)
AWS analytics stack and Well-Architected (Analytics, Security) for BFSI
UK / EU credit & lending regulatory context (FCA, model governance, fair-lending / explainability) — strong plus
Familiarity with credit-bureau / scoring data products — strong plus

Experience

Key characteristics (ideally 4/4):

Hands-on data science at enterprise scale
Worked with financial-services / credit clients or in-house at a credit / lending company
Cloud hyperscaler experience (AWS preferred)
Technology consulting / client-facing delivery background

Role-specific characteristics:

7+ years hands-on data science, with real credit-risk / financial modeling
Experience building and validating models in a regulated, audited context
Led small data-science teams while still coding personally
Demonstrably comfortable doing the data-cleaning grunt work themselves, not just directing it

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python full stack empleos en madrid, md

Data Science Lead

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Director, Data Engineering (Capital Markets)

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