Machine Learning Scientist

• As a Machine Learning Scientist, your work will focus on building, training and deploying machine learning models (Classification, Deep Learning, Optimization, Natural Language Processing, Active Learning) using the most advanced technologies and models. You will be responsible for identifying and using the most appropriate data sources and modeling techniques to solve complex problems and drive measurable business value
• You will also help in building new products and solutions by driving a research agenda and development plan from ideation to prototyping to full productionisation in the team, and using opportunities to contribute to a vibrant department’s ML community
• Translate business needs into ML/AI challenges, creating targeted research plans and innovative models for both immediate impact and long-term value
• Develop and deploy state-of-the-art ML/AI solutions, including Deep Learning, to optimize and drive business value striking a right balance between friction and risks
• Drive the end-to-end execution of the ML/AI development process on specific products, from understanding product requirements, data discovery, model development and evaluation, to implementation of a full production pipeline
• Conduct data analysis with detailed metrics to improve data quality, do feature exploration, evaluate model’s performance, etc
• Build, support and maintain readable and reusable code for both data processing and model training pipelines, using the right technologies and coding methodologies applying knowledge of business area tools and product needs
• Maintain a highly cross-disciplinary perspective, solving issues by applying approaches and methods from across a variety of ML/AI disciplines and related fields
• Support others through evidence and clear communication, explaining advanced technical concepts in simpler terms
• 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

Benefits

• Health insurance
• Free access to Headspace for you and your loved ones
• Global Employee Assistance Program
• Meditation and Breastfeeding rooms at the office
• Booking Cares - 2 days per year to volunteer and learn
• Life insurance
• Disability insurance
• Pension plan
• Annual paid time off
• Parental leave - 22 weeks
• Grandparent leave - 10 days
• Care leave - 10 days
• Bereavement leave - up to 4 weeks
• Anniversary leave
• Working from Home Furniture and Ergonomic Support
• Working from Abroad - up to 20 days per year
• Discounts & Wallet credits to spend on our products
• Upgrade to Booking.com Genius Level 3
• Friends & Family Booking.com discount vouchers
• Free access to online learning platforms
• Development and mentorship programs to support career growth
• Access to trainings and workshops
• Team development opportunities
• Local discount programs
• Game rooms in offices
• On-site meals, coffee and snacks including vegan options- Ability to define a machine intelligence strategy on a specific product by identifying short-term development steps that create immediate business value and build upon each other to create longer-term differentiation
• Strong working knowledge of Python
• Experience in big data technologies (MapReduce, Hadoop, AWS, SQL, Spark or similar technologies)
• Relevant work or academic experience (MSc + 3 years of working experience, or PhD), involved in the development and application of Machine Learning
• We have found that people who match the following requirements are the ones who fit us best:
• Advanced knowledge and experience in Classical Machine Learning, Statistics, Deep Learning, Optimization or similar
• Ability to drive and execute end-to-end research and development plans and generate impact through large-scale machine learning model development
• Successfully driving technical, business and people related initiatives that improve productivity, performance and quality while communicating with stakeholders at all levels
• Excellent English communication skills, both written and verbal