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Data Scientist

SiteMinder

🌍 Asia 🏠 Remote ⏱ Part-time 💼 Mid-level 🗓 2 weeks ago

At SiteMinder we believe the individual contributions of our employees are what drive our success. That’s why we hire and encourage diverse teams that include and respect a variety of voices, identities, backgrounds, experiences and perspectives. Our diverse and inclusive culture enables our employees to bring their unique selves to work and be proud of doing so. It’s in our differences that we will keep revolutionising the way for our customers. We are better together!

What We Do…

We’re people who love technology but know that hoteliers just want things to be simple. So since 2006 we’ve been constantly innovating our world-leading hotel commerce platform to help accommodation owners find and book more guests online - quickly and simply.

 

We’ve helped everyone from boutique hotels to big chains, enabling travellers to book igloos, cabins, castles, holiday parks, campsites, pubs, resorts, Airbnbs, and everything in between.

 

And today, we’re the world’s leading open hotel commerce platform, supporting 50,000 hotels in 150+ countries - with over 130 million reservations processed by SiteMinder’s technology every year.

About the Data Scientist role…

As a Data Scientist, you will play a pivotal role in building and scaling machine learning solutions that drive product intelligence and data-informed decision-making across SiteMinder. You will work closely with Principal Data Scientists and the Core Data Lab team to develop, validate, and productionise models that deliver real business impact. In collaboration with Engineering, you will focus on integrating models into products and tackling complex data science challenges related to prediction, recommendation, and optimisation.

What you’ll do…

- Design and develop end-to-end ML solutions — from data exploration and feature engineering to model training, validation, and deployment.

- Collaborate cross-functionally with engineers, analysts, and product teams to integrate predictive and recommendation models i...

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