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# Machine Learning Scientist II

- **Company:** Expedia, Inc.
- **Location:** London, UK
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** A/B Testing, Amazon Web Services, Big Data, Apache Hadoop, Python (Programming Language), Machine Learning, Tensorflow, Software Deployment, Cloud Platform System, Apache Spark, Keras, Pyspark, Scikit Learn, Information Technology, Machine Learning Operations, Software Library
- **Published:** June 3, 2026
- **Apply:** https://uk.indeed.com/viewjob?jk=77b181bda768904b

## About the Role

Do you have a Master's degree?, * Ph.D. (preferred) or master's degree in computer science, Machine Learning, Mathematics/Statistics or another related field of science.

 * 2 years of industry experience in applying ML to real-world problems desirable but not required.

 * Proficiency in Python , with experience using PySpark and common machine learning libraries and frameworks (e.g., scikit-learn, TensorFlow, Keras etc.).

 * Familiarity with big data technologies (e.g., Hadoop, Spark) and cloud computing platforms (AWS, GCP)

 * Solid understanding of common machine learning algorithms

 * Knowledge of statistics and probability theory

 * Excellent problem-solving skills and ability to learn new concepts quickly

 * Strong communication skills and ability to explain complex technical concepts to non-technical stakeholders

 * Enthusiasm for tackling challenging problems and contributing to innovative solutions

Accommodation requests

## Description

* Develop and implement ML models for recommendations & relevance at scale that can handle high-throughput, low-latency personalized recommendations across diverse partner segments within Expedia Group's B2B division.
 * 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.


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