Machine Learning Scientist II: Scalable Personalization

Expedia Group; Comunidad de Madrid; On-site; EUR 43,000 - 61,000; Full time

Benefits offered by this job

Medical coverage

Dental coverage

Vision coverage

Paid time off

Wellness stipend

Travel reimbursement

IATAN membership

Job summary

Expedia Group in Madrid is seeking a Machine Learning Scientist II to build end-to-end ML solutions for personalized recommendations, learning-to-rank, and relevance optimization within the B2B ML Science team. You will design models that scale for high-throughput, low-latency environments and work across partner segments.

The role emphasizes experimentation, A/B testing, collaboration with cross-functional teams, and clear communication of results to both technical and non-technical audiences.

Qualifications

• Ph.D. preferred or Master’s in computer science, ML, mathematics or statistics.
• 2 years of industry ML experience desirable but not required.
• Proficiency in Python with PySpark and ML libraries (scikit-learn, TensorFlow, Keras).
• Familiarity with Hadoop, Spark and cloud platforms (AWS, GCP).
• Solid understanding of ML algorithms; knowledge of statistics.
• Strong problem-solving and communication skills.

Responsibilities

• Develop and deploy ML models for recommendations and relevance at scale.
• Design and run A/B tests to improve algorithm performance.
• Collaborate with cross-functional teams to translate business needs into tech solutions.
• Communicate methodologies and results clearly to technical and non-technical audiences.

Skills

Python

PySpark

scikit-learn

TensorFlow

Keras

ML algorithms

Statistics

Communication

Education

PhD preferred

Master's in CS/ML/Math/Stats

Tools

Hadoop

Spark

AWS

GCP

Job description

Expedia Group in Madrid is seeking a Machine Learning Scientist II to build end-to-end ML solutions for personalized recommendations, learning-to-rank, and relevance optimization within the B2B ML Science team. You will design models that scale for high-throughput, low-latency environments and work across partner segments.

The role emphasizes experimentation, A/B testing, collaboration with cross-functional teams, and clear communication of results to both technical and non-technical audiences.