Senior Data Scientist

ZABEL; Barcelona; On-site; EUR 55,000 - 95,000; Full time

Job summary

ZABEL is looking for a Senior Data Scientist (m/f/d) to join its fast-growing product-driven Data Science team in Barcelona. You will own end-to-end ML projects, turning complex business problems into scalable models that directly influence product decisions, customer experience and commercial performance.

The role requires strong Python and SQL, expertise in classical ML, and a product- and business-first mindset.

Qualifications

• 4+ years of commercial Data Science experience.
• Strong Python and SQL skills.
• Solid experience with classical Machine Learning, statistics and predictive modelling.
• Experience owning ML projects from problem definition through deployment and measuring business impact.
• Strong stakeholder management and communication skills.
• A product and business-first mindset.
• Experience working with large-scale datasets in production environments.
• The ability to translate ambiguous business challenges into scalable ML solutions.

Responsibilities

• Design, build and deploy scalable machine learning models into production.
• Develop predictive models for pricing, forecasting, ranking, recommendations, churn prediction, customer segmentation and revenue optimisation.
• Analyse large, complex datasets to uncover business opportunities.
• Design, execute and evaluate A/B tests and other online experiments.
• Continuously monitor, improve and retrain production models.
• Partner with Product Managers, Software Engineers, Data Engineers and business stakeholders to deliver measurable outcomes.
• Drive projects from problem definition through deployment and monitoring.
• Contribute to technical strategy, best practices and knowledge sharing within the Data Science organization.

Skills

Python

SQL

Machine Learning

Stakeholder management

Product mindset

Large datasets

Job description

Senior Data Scientist (m/f/d) – Machine Learning & AI

Employment Type: Full-time

Drive AI Innovation at Scale:

I'm currently partnering with one of Europe's fastest-growing consumer tech marketplace companies to find a Senior Data Scientist to join a high-impact, product-led Data Science team.

This is a role for someone who enjoys solving complex business problems with machine learning and seeing their work directly influence product decisions, customer experience and commercial performance. You'll own projects end-to-end, collaborating closely with Product, Engineering, Analytics and business stakeholders to deliver measurable impact.

We're particularly looking for candidates with strong expertise in one of the following domains:

• Dynamic Pricing & Revenue Management
• Ranking & Recommendation Systems

You'll Be a Great Fit if You Have:

• 4+ years of commercial Data Science experience
• Strong Python and SQL skills
• Solid experience with classical Machine Learning, statistics and predictive modelling
• Experience owning ML projects from problem definition through deployment and measuring business impact
• Strong stakeholder management and communication skills
• A product and business-first mindset
• Experience working with large-scale datasets in production environments
• The ability to translate ambiguous business challenges into scalable ML solutions

Experience in One or More of the Following Areas Is Highly Desirable:

• Dynamic Pricing
• Revenue Management
• Forecasting
• Ranking
• Recommendation Systems

Your Responsibilities:

• Design, build and deploy scalable machine learning models into production.
• Develop predictive models for pricing, forecasting, ranking, recommendations, churn prediction, customer segmentation and revenue optimisation.
• Analyse large, complex datasets to uncover business opportunities.
• Design, execute and evaluate A/B tests and other online experiments.
• Continuously monitor, improve and retrain production models.
• Partner with Product Managers, Software Engineers, Data Engineers and business stakeholders to deliver measurable outcomes.
• Drive projects from problem definition through deployment and monitoring.
• Contribute to technical strategy, best practices and knowledge sharing within the Data Science organization.