Research Analyst à United States

Introduction to the team

Private Label Solutions (PLS) is the B2B arm of Expedia Group. We bring Expedia Group's innovative technology and distribution solutions to partners across the world. These businesses include global financial institutions, corporate managed travel, offline travel agents, global travel suppliers (like major airlines) and many more …

We are looking for a ML Scientist II to join the Private Label Solutions (PLS) Machine Learning Science. You will join a team that builds end-to-end ML solutions for various business problems, contributing substantial value for our partners and for EG. We embrace test and learn by continuously experimenting, analyzing and improving our algorithms which has helped the B2B business become one of the fastest growing at Expedia Group.

This applied scientist role will join our ML team at Expedia Group. This role offers a unique opportunity to work on diverse challenges and contribute to cutting-edge solutions that drive significant impact for the business. You will gain expertise in commercial acumen, engineering, analysis, and applied machine learning at scale.

This role requires an individual that has a solid foundation in machine learning and engineering, is passionate about driving meaningful impact whilst being mindful of the broader context in which their work sits, is comfortable with ambiguity and enjoys the challenge of tackling open ended problems.

In this role, you will:

• Develop and implement ML models for a variety of business applications within Expedia Group’s B2B arm.

• Contribute to building and enhancing end-to-end ML solutions, from data preprocessing to production deployment.

• Design and run A/B tests and experiments to continuously improve algorithm performance.

• Stay current with the latest ML techniques and contribute to the team’s technical capabilities.

• Collaborate with cross-functional teams to translate business needs into technical solutions.

• Communicate methodologies and results clearly to both technical and non-technical audiences and work across the tech stack to deploy models.

Experience and qualifications:

• You hold a Ph.D. (preferred) or Master’s in Computer Science, Machine Learning, Mathematics/Statistics, or a related field.

• You have 2 years of industry experience applying ML to real-world problems (desirable but not required).

• You possess a solid understanding of machine learning algorithms, statistics, and probability theory.

• You demonstrate strong problem-solving skills, a quick learning ability, and enthusiasm for tackling complex challenges.

• You are proficient in Python, with experience using PySpark and ML libraries such as scikit-learn, TensorFlow, or Keras.

• You are familiar with big data technologies (e.g., Hadoop, Spark), cloud platforms (AWS, GCP), and can effectively communicate technical concepts to non-technical stakeholders.