Data Scientist: ML & Analytics for Customer Impact

Matrix Usa Inc; Madrid; On-site; EUR 50,000 - 65,000; Full time

Job summary

Matrix Usa Inc seeks a highly motivated Data Scientist to join our growing team. You will work with large-scale datasets, develop advanced analytical models, and collaborate with product, engineering, and business stakeholders to drive measurable impact.

This customer-facing role emphasizes practical analytics, end-to-end model development, deployment, and knowledge transfer. You will help translate complex data problems into actionable solutions across finance and operations.

Qualifications

• Bachelor's degree in a quantitative field.
• 2+ years in Data Science, Data Engineering, ML, or Big Data development.
• Strong Python and PySpark skills.
• Experience with large-scale data processing frameworks and ML pipelines.
• Experience with ML lifecycle tools such as MLflow or Airflow.

Responsibilities

• Design and implement data science solutions across the project lifecycle.
• Analyze large datasets to identify trends, anomalies, and insights.
• Develop and optimize ML models and analytics workflows.
• Perform feature engineering and data prep for predictive modeling.
• Collaborate with Product, Engineering, and Customer Success to translate requirements into solutions.
• Lead data science aspects of customer implementations and deployments.
• Build technical relationships with customers and partners.
• Provide recommendations to improve products and algorithms.
• Deliver training and knowledge transfer to end users.

Skills

Python

PySpark

MLflow

Airflow

SQL

Statistical Analysis

Education

Bachelor's degree in Data Science/CS/Math/Stats/Economics

Tools

MLflow

Airflow

Job description

Matrix Usa Inc seeks a highly motivated Data Scientist to join our growing team. You will work with large-scale datasets, develop advanced analytical models, and collaborate with product, engineering, and business stakeholders to drive measurable impact.

This customer-facing role emphasizes practical analytics, end-to-end model development, deployment, and knowledge transfer. You will help translate complex data problems into actionable solutions across finance and operations.