Do you want to power the future of travel? Then come and make a positive impact, strengthen connections, and bridge divides across the world, at Expedia Group. You can help us bring people together through travel technology, while jump-starting your career in Machine Learning Science.

Travel is so much more than simply reaching your destination. Along your journey you will make an immediate impact on reimagining the way people search for travel and invent new techniques to help travelers find the right pathways through millions of possibilities. From prototyping new ML models with A/B testing to applying new techniques to services that run tens of thousands of requests per second, there’s no shortage of opportunities to innovate at Expedia Group!

We are hiring across multiple teams, therefore the role may differ dependent on this. Sound interesting? Then check out what our current graduates are working on, below!

Joanna Krodkiewska, Machine Learning Scientist in London

Tell us about your team

“I’m part of the AI and Data Science organization which works on building, deploying, and maintaining machine learning models with various applications across Expedia Group (EG), such as hotel search rank, image rank for properties’ images and fraud detection. The team I’m working in is Content AI & ML. The team uses machine learning to build models around the content display on EG websites. The three main areas are: computer vision (anything to do with images displayed on the websites), NLP (working with text data) and structured content such as hotel amenities.”

Tell us about your role

“I’m currently working with structured data only but I’m looking to get involved with NLP problems in the future as well. The typical tasks I’m working on involve data cleaning, feature engineering and evaluating model performance as well as working on building and improving data pipelines.”

What skillsets do you think are required to be successful in your role?

“I would say you need a theoretical understanding of machine learning and various classification and regression algorithms. A second, and equally important, component is coding skills as well as having experience implementing some simple ML models.”

What technologies and languages do you work with?

“I  work mostly with Spark, Python and Scala.”

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Samuil Stoychev, Machine Learning Scientist in London

Tell us about your team

“I am part of the Revenue Optimisation and Data Science team. Like the name suggests, we apply data science approaches to optimise processes related to Expedia Partner Solutions (EPS), such as package pricing and TAAP. In terms of team organisation, my team consists of 2 managers and around 10 machine learning scientists.”

Tell us about your role

“My role in the team is a Machine Learning Scientist. I mostly work on algorithm development – experimenting with new models for package pricing. It is a fairly technical role – so I spend perhaps 50% of my time in coding, deployment and running experiments.”

What skillsets do you think are required to be successful in your role?

“In terms of skillset required, I think coming from a STEM background is definitely helpful – I have occasionally found myself in situations where I feel I would have struggled if I didn’t have at least some mathematical background. I would say basic coding skills are also a prerequisite, and it is also good to have good communication skills – especially the ability to articulate and present findings.”

What technologies and languages do you work with?

“The main programming language we use in our team is Python (and Python-based libraries – e.g., Tensorflow, Keras, scikit-learn, numpy, etc.). We occasionally use Scala, but I would not say it is a must-have, and most people have no prior Scala experience when they join. Other technologies we use heavily are Databricks, Tableau, Git – however, I think those could be easily learnt on the go by new joiners (I personally hadn’t used Databricks or Tableau before joining Expedia Group).”

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Jack Pennington, Machine Learning Scientist in London

Tell us about your team

“I’m in the Personalization & Recommendations Team and within that I’m on the Intents team. We work on predicting user intentions on our platform. These could be:

Are they going to book? What line of business are they interested in? Location? Hotel vs. Vacation Rental? By the beach? Near a museum? Using this information we can personalise their UX, therefore increasing conversions and increasing revenue.”

Tell us about your role

“I’m a Machine Learning Scientist, and currently I’m working on a project called Digital Experience Score (Struggle Score) which is an AI-based approach to measure and detect friction and task success in all EG user experiences. Alongside that I’m working on refactoring our training pipeline for the intent prediction, and creating a data extraction pipeline to extract data from clickstream. I’m also working with the Clickstream product team to get telemetry events added to clickstream.”

What skillsets do you think are required to be successful in your role?

“A strong mathematical background, knowledge of Machine Learning, programming fundamentals, problem solving and taking initiative.”

What technologies and languages do you work with?

“Languages: Scala, Python, SQL

Frameworks/Libraries: Spark (Scala/ PySpark), Tensorflow, Python Packages (Numpy, Pandas, Matplotlib etc.)

Tools: AWS, Databricks, Git”

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Kaia Bonnet, Machine Learning Scientist in Geneva

Tell us about your team

“We are in the Data Science and Analytics organization. The Scout team is working on machine learning algorithms to help our supply partners and support market managers.”

Tell us about your role

“Our role is to develop and maintain machine learning algorithms that respond to business needs. We are working closely with engineers and stakeholders (mostly market management teams). It’s important we understand the business need and help to translate this into a machine learning problem and propose a solution. A lot of the work is also related to tweaking existing algorithms for new requirements and fixing bugs that may arise.”

What skillsets do you think are required to be successful in your role?

“Have a strong foundation in machine learning to understand the models and propose the best solutions. Previous experience with coding to be able to develop and maintain the algorithms. Good communication skills to understand the need of stakeholders and explain the technical solutions and possible limitations. Someone who likes to learn because this field is evolving fast, so there will always be a need to learn new tools and more theory.”

What technologies and languages do you work with?

“Python and SQL. Distributed environments like Spark. The cloud services we use are Databricks and Qubole.”

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Hannah Grandine, Machine Learning Scientist in Seattle

Tell us about your team

“I work for the Fraud Machine Learning team within E-Commerce and Fraud & Risk, which is the group that is responsible for creating and maintaining all fraud detection and prevention models across the Expedia brands.”

Tell us about your role

“I am a Machine Learning Scientist. My primary responsibilities are to generate and perform experiments to improve the existing machine learning models and to create new models and ideas to better prevent fraud.”

What skillsets do you think are required to be successful in your role?

• “A basic understanding of data science, machine learning, and statistical techniques including XGBoost, Linear/Logistic Regression, ensemble methods, and model evaluation
• Proficient in data wrangling using advanced SQL queries and Python
• Data visualization and model training using Python
• Effective communication skills
• Ability and desire to learn new machine learning techniques and other computing skills regularly as part of the job”

What technologies and languages do you work with?

“SQL/Hive, Python, Jupyter, AWS, XGBoost, pandas, numpy, Excel, bash, JSON.”

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Machine Learning Scientist Graduates do not join our typical Graduate Program format (including team rotations), due to their level of technical expertise. Instead they join our 1st Year Experience, which includes access to tech learning communities, panel discussions, and development opportunities through skill-builder courses.

We’re looking for outstanding talent to join us on our mission to power global travel for everyone, everywhere. Take a look at our latest Early Careers opportunities here.