We believe that travel is a force for good. Our advanced technology helps travelers everywhere create amazing journeys, and our Artificial Intelligence and Machine Learning tools power unforgettable personalized experiences. Every day, we find new ways to combine our industry knowledge with advanced tech solutions to build a more open world for everyone, everywhere.

In this blog we go behind the scenes to learn about the work of Machine Learning Scientist III, Catriona Mitchison. Discover how her research contributes to our cutting-edge features and products and how EG has supported her career growth.

Tell us about your role and team.

I am a Machine Learning Scientist III and I work on the algorithm side. My job is to research, design and develop algorithms to estimate the causal impact of a property taking an action on our platform. I leverage the latest research in Causal Inference to ensure our properties have as accurate an idea of how they could improve their property’s performance with us. My job is fascinating! I get to implement algorithms that have real impact for businesses, while being at the cutting edge of the technology that is being developed in our field.

Typically, at the start of (and often throughout) a project I will spend my time understanding the business need, the product I am trying to estimate the impact of and the constraints within which I must work (infrastructure, data volume, data quality etc.). The iteration with business is pivotal: an algorithm, no matter how perfect, that answers a question nobody is asking, is useless. I then spend some weeks building the algorithm, before liaising closely with Machines Learning Engineers to deploy these algorithms in production.

Can you share an experience where EG supported your professional development?

EG encourages paper submissions: whenever a project completes, our organization invites you to look at how this contributes to the community and see if it could be put forward for a conference submission. It’s always up to you to ensure that you are leaving enough time for yourself to write them, which can sometimes be tricky in a busy business environment, but the culture is very much encouraging of it.

My latest paper was on the topic of measuring platform level incrementality. I co-submitted it, along with Florian Hatt, recently to the Knowledge and Data Discovery (KDD) conference in Barcelona. It’s an exciting new area of research for us and we proposed a novel method to measure platform level incrementality: combining multiple uplift models at difference levels of aggregation to achieve a final incrementality factor.

I had been working on this project for a long time, incrementally increasing the scope and depth of the analysis, when my manager encouraged me to submit it to a conference workshop on Causality. As far as we could tell, this approach had never been used before, so I was well into the realm of the experimental. Upon successful completion of the project and submission, the paper got accepted for KDD conference in Barcelona where I got to present it!

Can you tell us more about this year’s KDD conference and EG’s presence there?

KDD was an invigorating week spent connecting with ML Scientists from across EG and other tech companies, exploring the key subjects in artificial intelligence and exchanging ideas. Specifically, sessions on Interpretability & Trustworthiness in LLMs, Controlled Experimentation frameworks and Two-sided Marketplace Optimization are extremely salient to EG, and the value of remaining on top of latest research in the area is immense. EG’s presence at KDD shows the company’s commitment to innovation and remaining at the cutting edge of Machine Learning and Artificial Intelligence.

At this year’s conference, our presence was really felt! From me leading a workshop called Causality and Machine Learning in Business to our vibrant and enthusiastic team, we had curious people bustling around our booth every day, keen to hear about what we were getting up to.

Why would you recommend working at EG?

My tenure speaks to my appreciation of the EG working environment. Between the people, who’s collaborative and intelligent nature make them a pleasure to work with; the projects, which are varied and innovative, provide real business value and are at the more advanced edge of machine learning; and the company itself, making tangible efforts to value employees through inclusion programs, professional development, healthcare, parental benefits and flexible working conditions. There’s a lot keeping me here.

On the development front, Expedia Group encourages continuous learning, and have implemented numerous policies to enable that, including financially supporting me to complete courses, and a Day of Learning once a month, where you can focus on whatever development topic you choose. As a Machine Learning Scientist, I have come along in leaps and bounds since I started here, taking courses in NLP, Causality and becoming proficient in spark, entirely due to the projects I have worked on and the learning that EG has funded.

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