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# Data Lead

- **Company:** Mscope
- **Location:** Madrid, Spain
- **Contract:** Permanent contract
- **Skills:** Microsoft Excel, Amazon Web Services, Amazon S3, Data Analysis, Big Data, Information Engineering, Database Queries, Distributed Computing Environment, Distributed Data Store, Python (Programming Language), Machine Learning, Recommender Systems, Reinforcement Learning, Pyspark, Data Analytics, Terraform, Data Pipelines, Docker
- **Published:** September 29, 2026
- **Apply:** https://www.buscojobs.com.es/data-lead-en-madrid-ID-373540529

## About the Role

What we're looking for Strong quantitative and analytical mindset , comfortable translating business criteria into scoring and prioritisation logic.
At least 5 years of experience in data-intensive roles (Data Engineering, Analytics or Data Science), with at least 2 years leading or coordinating technical teams.
Solid experience designing and operating AWS cloud architectures for data workloads (S3, Glue, Lambda, Step Functions, Athena, RDS).
Expert knowledge of Python for data engineering and analytical applications; SQL proficiency for complex querying and data modelling.
Demonstrated experience building scoring, prioritisation or recommendation systems that combine business rules with data-driven models (next-best-action, lead scoring, opportunity prioritisation, or equivalent).
Fluency in Spanish and English.
This gives extra points Background in Mathematics, Operations Research, Statistics, or other quantitative disciplines.
Hands?on experience with constrained/combinatorial optimisation, multi?armed bandits, or reinforcement learning applied to business decisioning.
Experience with Big Data frameworks (PySpark, Glue ) and distributed data processing.
Relevant experience with CI/CD pipelines, infrastructure-as-code (Terraform/CDK ), and container environments (Docker, ECS).
Experience in Financial Services, banking CRM/commercial platforms, credit risk, or marketing decisioning .
Previous experience in a startup or fast?paced environment building multi?country/multi?tenant products from scratch, where ownership and autonomy are key.
What we offer 25 days of vacation (and your birthday off! ) Hybrid mode: 2 days in office 3 days in remote #J-*****-Ljbffr

## Description

The role Build the prioritisation engine: business rules, objective function and expected-value scoring per company/product.Architect data pipelines on AWS (Glue, Step Functions, Lambda, S3, Athena, Bedrock) that replace static lists and manual CRM/Excel crosses with automated opportunity identification.Lead a cross-functional team of Data Engineers and Data Scientists , mentoring them on architecture, data quality and the integration of scoring/ML models into production.Build full traceability into the system , target perimeter vs. covered perimeter.Design the criteria-governance and market-intelligence layers as a reusable standard across business units, banks and countries.Collaborate closely with Product and Business teams to turn real banking pain points into a robust, sellable product.What we're looking for Strong quantitative and analytical mindset , comfortable translating business criteria into scoring and prioritisation logic.At least 5 years of experience in data-intensive roles (Data Engineering, Analytics or Data Science), with at least 2 years leading or coordinating technical teams.Solid experience designing and operating AWS cloud architectures for data workloads (S3, Glue, Lambda, Step Functions, Athena, RDS).Expert knowledge of Python for data engineering and analytical applications; SQL proficiency for complex querying and data modelling.Demonstrated experience building scoring, prioritisation or recommendation systems that combine business rules with data-driven models (next-best-action, lead scoring, opportunity prioritisation, or equivalent).Fluency in Spanish and English.This gives extra points Background in Mathematics, Operations Research, Statistics, or other quantitative disciplines.Hands?on experience with constrained/combinatorial optimisation, multi?armed bandits, or reinforcement learning applied to business decisioning.Experience with Big Data frameworks (PySpark, Glue ) and distributed data processing.Relevant experience with CI/CD pipelines, infrastructure-as-code (Terraform/CDK ), and container environments (Docker, ECS).Experience in Financial Services, banking CRM/commercial platforms, credit risk, or marketing decisioning .Previous experience in a startup or fast?paced environment building multi?country/multi?tenant products from scratch, where ownership and autonomy are key.What we offer 25 days of vacation (and your birthday off! ) Hybrid mode: 2 days in office 3 days in remote #J-*****-Ljbffr


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