|Job Type:||Full Time|
Are you keen to make a difference in a dynamic organisation? Hotels.com is seeking for a highly motivated and analytical individual as our new Lead Data Scientist to help us lead and optimize using machine learning and AI techniques to match our customer needs with the lodging supply options available in our two-sided marketplace.
Reporting to the Principal Data Scientist, this position is a senior role within the Hotels.com Data Science team. In this role, you will lead key ML projects and become part of the team focused to improve our Content and Recommendations. You will be working with one of the world's largest travel data environments and will have an opportunity to make a massive impact and influence key strategic decisions.
What you will do:
You will drive machine learning and optimization efforts to help improve how we i) collect and influence customer intent, ii) understand the relevant product options and iii) rank those options
You will lead key projects and apply machine learning, data mining and statistical modelling to design and implement mathematical models and algorithms to solve real-world applications
You will contribute to Hotels.com’s & Expedia Group's wider data science efforts – an area of major focus for the company
You will run A/B test design, implementation and analysis on the website to find out the effectiveness of our efforts
Stay up to date with the latest data science/ ML / AI technologies and techniques and identifying and advising how they can be utilized throughout the range of potential use cases
Who you are:
Between 5 and 10 years experience in data science and machine learning roles especially in Recommender Systems, Computer Vision or NLP.
MS or PhD degree in a highly quantitative field such as Economics, Mathematics, Statistics, Engineering, Machine Learning/AI
Deep understanding of methods such as Learn to Rank, Recommender Systems, Personalisation, Classification, Deep Learning, Clustering, Factor Analysis, Regression, Predictive Modelling, Numeric Optimization etc.
Clear track record of turning analytics/ ML into action
Experience with statistics/machine learning packages such as Keras, Tensorflow or Spark MLlib. Experience with programming in Python or Scala.
Excellent written and oral communication skills, including an ability to communicate across business areas
Why join us:
Expedia Group recognizes our success is dependent on the success of our people. We are a global travel platform, made up of the most knowledgeable, passionate, and
creative people in our business. Our brands recognize the power of travel to break down barriers and bring the world within reach – that responsibility inspires us to be the place where exceptional people want to do their best work, and to provide them the tools to do so.
Whether you're applying to work in engineering or customer support, marketing or lodging supply, at Expedia Group we act as one team, working towards a common goal; to bring the world within reach. We relentlessly strive for better, but not at the cost of the customer. We act with humility and optimism, respecting ideas big and small. We value diversity and voices of all volumes. We are a global organization but keep our feet on the ground so we can act fast and stay simple. Our teams also have the chance to give back on a local level and make a difference through our corporate social responsibility program, Expedia Cares.
If you have a hunger to make a difference with one of the most loved brands in the world and to work in the dynamic travel industry, this is the job for you.
Our family of travel brands includes: Brand Expedia®, Hotels.com®, Expedia® Partner Solutions, Egencia®, trivago®, Vrbo®, Orbitz®, Travelocity®, Wotif®, ebookers®, CheapTickets®, Hotwire®, Expedia® Media Solutions, CarRentals.com™, Expedia Local Expert®, Expedia Cruises™ and SilverRail Technologies, Inc. For more information, visit www.expediagroup.com.
Expedia is committed to creating an inclusive work environment with a diverse workforce. All qualified applicants will receive consideration for employment without regard to race, religion, gender, sexual orientation, national origin, disability or age.