Role Description:
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 Intent Discovery track 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.
Qualifications & Skills:
Masters, PhD, or equivalent experience in a quantitative field (Computer Science, Mathematics, Engineering, Artificial Intelligence, etc.).
At least 3 years of relevant work experience.
Experience with TensorFlow/PyTorch is a strong 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 experimental design, A/B testing, and evaluation metrics for ML models.
Excellent communication and collaboration skills to work effectively with diverse crafts such as engineering, UX, and product management.
Experience working on complex multi-stage recommender architectures is a strong plus.
Booking.com’s Total Rewards Philosophy is not only about compensation but also about benefits. We offer a competitive , as well unique-to-Booking.com benefits which include:
Annual paid time off and generous paid leave scheme including: parental (22-weeks paid leave), grandparent, bereavement, and care leave
Hybrid working including flexible working arrangements, working from home furniture and ergonomic support, and up to 20 days per year working from abroad (home country)
A beautiful sustainable , that offers on-site meals, coffee, and snacks, multi-faith and breastfeeding rooms at the office*
Commuting allowance and bike reimbursement scheme
Discounts & Wallet credits to spend on our products, upgrade to Booking.com Genius Level 3, and friends & family Booking.com discount vouchers
Free access to online learning platforms, development and mentorship programs
Global Employee Assistance Program, free Headspace membership
Application Process
Let’s go places together:
The interview process entails: 1. "On the spot" Business Case Interview, 2. "Take home" Business case Interview, 3. Final behavioral interview
This role does not come with relocation assistance.
Pre-Employment Screening
If your application is successful, your personal data may be used for a pre-employment screening check by a third party as permitted by applicable law. Depending on the vacancy and applicable law, a pre-employment screening may include employment history, education and other information (such as media information) that may be necessary for determining your qualifications and suitability for the position.
