Travel Tech Data Scientist: Predictive Analytics & ML

Traveltechessentialist; Barcelona; Híbrido; EUR 40.000 - 60.000; Jornada completa

Descripción de la vacante

A leading travel technology company in Barcelona is seeking an experienced Data Scientist to join their Data Science Team. In this role, you will conduct predictive analytics, collaborate with various teams to embed machine learning in products, and design advanced analytical solutions for travel-related challenges. The ideal candidate has a degree in a quantitative field and strong experience in Python, SQL, and machine learning frameworks. This position offers competitive compensation, opportunities for continuous learning, and a flexible work environment.

Servicios

Flexible benefits

Performance-based bonuses

Birthday day off

Continuous learning opportunities

Work-life balance initiatives

Formación

• 2+ years of related experience as a Data Scientist or Machine Learning engineer.
• Strong experience coding in Python and solid understanding of statistical methods.
• Experience using frameworks like Spark and Tensorflow; solid knowledge of SQL.

Responsabilidades

• Conduct predictive analytics to understand customer interactions.
• Collaborate with teams to embed Machine Learning into products.
• Stay up to date with developments in Machine Learning technologies.

Conocimientos

Python

Machine Learning

Analytical skills

SQL

Big Data technologies

Educación

Degree in a quantitative field

Herramientas

Spark

Tensorflow

scikit-learn

pandas

Descripción del empleo

A leading travel technology company in Barcelona is seeking an experienced Data Scientist to join their Data Science Team. In this role, you will conduct predictive analytics, collaborate with various teams to embed machine learning in products, and design advanced analytical solutions for travel-related challenges. The ideal candidate has a degree in a quantitative field and strong experience in Python, SQL, and machine learning frameworks. This position offers competitive compensation, opportunities for continuous learning, and a flexible work environment.