Machine Learning Scientist II - Customer centric data

at  Bookingcom

At Booking.com, data drives our decisions. Technology is at our core. And innovation is everywhere. But our company is more than datasets, lines of code or A/B tests. We’re the thrill of the first night in a new place. The excitement of the next morning. The friends you make. The journeys you take. The sights you see. And the food you sample. Through our products, partners, and people, we make it easier for everyone to experience the world.

ROLE DESCRIPTION

Ensuring we understand the needs and intentions of our travelers remains a top priority for Booking. With millions of accommodations, flights, taxis, attractions, and car rentals available on our platform, our aim is to assist customers in finding the perfect fit for their journey. Customers may express their needs and intentions directly through their searches or filter usage, while in addition we can further deduct their preferences from their interactions on our platform, such as clicking on specific accommodations rather than others. At Booking, we consistently analyze and model customer behavior to personalize the traveler experience.
Following successful user intent and needs modeling across various parts of the company, these efforts have recently been consolidated into a central team, and as part of the Traveler Centric Data track within the new Marketplace business unit we are now expanding further. The User Intent Modelling team is building upon past successes, while also deepening on innovation to push the boundaries for personalisation even further by leveraging state-of-the-art Machine Learning and Artificial Intelligence. It is a crucial aspect of the Marketplace vision to ensure we guide our travelers to the most suitable products and facilitate seamless connections between the various parts of their trip.
As a Machine Learning Scientist, you will be developing state-of-the-art Machine Learning models, owning the design and delivery of ML systems, from initial idea-generation, collecting business requirements from product stakeholders to implementation. You will work closely together with the other Machine Learning Scientists and Machine Learnings Engineers in the User Intent Modelling team as well as with Data Engineers, Software Engineers and Product Managers.

KEY JOB RESPONSIBILITIES AND DUTIES

• Work in a multi-disciplined team where you’ll take full ownership of turning discoveries and ideas into products through machine learning (incl. understanding product requirements, data discovery, model development and evaluation, to implementation of a full production pipeline for both batch and stream-based deployment).
• Use the ML model’s output to deliver both short-term commercial impact and longer-term differentiated business value and customer experience.
• Define and build proof-of-concepts to test new ideas and demonstrate their potential value to relevant stakeholders.
• Develop production-grade ML code for models, features, and pipelines, accounting for scalability, latency, realtime requirements, monitoring and retraining.
• Build readable and reusable code, using the right technologies and coding methodologies applying knowledge of business area tools and product needs.
• Continuously evolve your craft by keeping up to date with the latest developments in ML/AI and related technologies, and upskilling on these as needed.
• Actively contribute to Machine Learning at Booking.com through training, exploration of new technologies, interviewing, onboarding and mentoring colleagues.

ROLE QUALIFICATIONS AND REQUIREMENTS

• At least years of relevant work experience.
• Masters, PhD, or equivalent experience in a quantitative field (Computer Science, Mathematics, Engineering, Artificial Intelligence, etc.).
• We prefer candidates with Deep Learning experience, especially when applied to large-scale datasets. Experience with TensorFlow is a plus.
• Solid understanding of fundamental machine learning concepts.
• Fluency in at least one programming language, with a strong preference for Python.
• Strong working knowledge of Spark and SQL.
• Experience with putting machine learning models in production is a plus.
• Excellent English communication skills, both written and verbal; the ability to convey your message to team members and other stakeholders.