Cloudbeds is hiring a
ML Data Engineer

Summary

The job is for a Data Engineer at Cloudbeds, a global hospitality platform provider. The role involves building and implementing end-to-end features for revenue optimization using machine learning models. The employee will work closely with cross-functional teams to identify areas of improvement and develop solutions. The position is based in London, UK (Hybrid).

Requirements

• 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

Responsibilities

• Build and implement end-to-end features and functionality that allow our lodging customers to optimize their revenue
• 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

Benefits

• Flexible working schedules with an open Paid Time Away policy
• Opportunity to travel and work remotely with great people