ML Data Engineer - Revenue Management System (Hybrid) (United Kingdom)

Overview

Cloudbeds provides the platform that powers hospitality, driving streamlined operations, increasing reservations and revenue, and enabling memorable guest experiences for lodging businesses of all sizes and types. Named the No. 1 PMS and No. 1 Hotel Management System by Hotel Tech Report in , Cloudbeds is trusted by properties across the globe for its award-winning front desk, revenue, distribution, guest acquisition and guest engagement solutions seamlessly combined in a single unified system. 

Behind the Cloudbeds platform is a growing team of + employees distributed across 40+ countries speaking 30+ languages. From data architects to UX designers, integrations managers to payments experts, former hotel managers to former OTA executives, our team comprises the brightest minds in technology and hospitality working to solve the industry’s biggest challenges.

From the beginning, we've believed that our people are our greatest asset, so we founded the company as #RemoteFirst, #RemoteAlways with shared that allow our team to thrive. This means we:

Hire the best people around the world; Emphasize the value of results over hours put in; Provide flexibility in working hours and locations; Foster an inclusive environment that celebrates bold thinking and diverse perspectives; Offer open vacation policies, free LinkedIn Learning, and other benefits that promote well-being and professional development.

As aData Engineer, you will build and implement end-to-end features and functionality that allow our lodging customers to guide their pricing strategy. Some of these features will make use of simple heuristic data while others may involve some algorithmic or machine learning components. You will work closely with our product and engineering teams to identify areas of improvement and develop solutions to drive revenue growth for the hotels our customers operate. You will be responsible for the end-to-end development of our revenue management application.

Location:London, UK (Hybrid)

What You Will Do: 

Build and implement end-to-end features and functionality that allow our lodging customers to optimize their revenue, through making informed pricing decisions. Some of these features will make us of simple heuristic data while others may involve algorithmic or machine learning components Where needed, develop and implement machine learning models to optimize revenue generating opportunities for our customers Collaborate with cross-functional teams to identify areas for product improvement If needed, figure out ways to structure data to make it easy to analyze and apply learning algorithms Build and maintain data pipelines to extract and transform data from various sources Analyze data sets to identify trends and patterns that inform product development and marketing strategies Design and conduct experiments to test the effectiveness of new features and improvements Communicate findings and insights to stakeholders across the organization, including product, engineering, and customer success teams

You’ll Succeed With:

Bachelor's degree or higher in a quantitative field such as Computer Science, Statistics, Mathematics, or Data Science 3+ years of experience in a data engineering role, preferably in the hospitality industry Expertise deploying machine learning models on the Cloud at scale, e.g. using MLFlow Expert level knowledge of SQL and experience working with large datasets Expertise with AWS or other cloud computing platform Experience implementing machine learning models using Python, including familiarity with popular data science frameworks such as Pandas, Scikit-Learn Strong problem-solving skills and ability to think creatively about complex business problems Strong application development skills Excellent communication skills and ability to collaborate effectively with cross-functional teams

Our company culture supports flexible working schedules with an open Paid Time Away policy and gives all team members the opportunity to travel and work remotely with great people. If you think you have the skills and passion, we’ll give you the support and opportunity to thrive in your career. If you would like to be considered for the role, we would love to hear from you!