Machine Learning Manager - Ranking Team

About Us: 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 encounter. The journeys you take. The sights you see. And the memories you make. Through our products, partners and people, we make it easier for everyone to experience the world. Leadership/Team Quote: The Ranking team is powering the ordering of products across various touchpoints on the Booking.com platform, with a primary focus on optimizing search results. The team manages billions of requests daily, each of which relies on cutting-edge Machine Learning (ML) solutions to allow Booking.com customers to experience the world. Role Description: As the Machine Learning Manager, you will manage a team of ML scientists & engineers, Data scientists & engineers which all work on different aspects for ranking/recommendation of products at Booking.com. You will lead & own all related technical aspects of the ML based solution and collaborate with additional stakeholders (Engineering & Product) for providing the best outcome for our customers. As a technical manager, you should be passionate about technology, keep up to date with recent breakthroughs in the field, define and shape the team’s ML roadmap, and not be afraid to get your hands dirty with code when needed. As the ML manager of the team, you are expected to be the focal point for all technical aspects, make sure your team members deliver on their tasks, and work together with other stakeholders to define and shape the roadmap of our products. You will work independently and will also be responsible for making technical decisions within your team. When it comes to management, your expertise in handling people will motivate and inspire them to reach outstanding success! You should have experience in developing people. You will mentor and coach your team while working closely with a Product Manager. Key Job Responsibilities and Duties: Build a strong team within their area, by coaching and developing individual contributors Prioritize work in collaboration with Product Managers, depending on business needs and keeping stakeholders aligned at all times. Translate machine learning vision and strategy into planning and execution, and ensure timely delivery of their plans. Develop innovative ML models, algorithms, and engineering approaches or identify existing ones, with the potential to impact our business. Design and execute applied research plans to understand, apply, test, evolve, and generalise these technologies into reusable frameworks. Translate business problems into viable, reliable and robust ML and AI solutions, accounting for constraints of the production environment. Monitor product health, performance and business impact and act accordingly when requirements are not met. Identify underlying issues and opportunities across domains and situations that are not obviously related through application of structured thinking and logic. Solve issues by applying methods and insights gained from a variety of disciplines, navigating a variety of environments. Make things happen by maintaining motivation and conveying a sense of urgency, focusing on outcomes and accomplishments, while respecting the need to balance long- and short-term goals, by applying influencing techniques and decision making skills. Drive, coach and mentor others through evidence and clear communication, explaining advanced technical concepts in simpler terms. Continuously evolve your craft. Keep up to date with industry and academic standard methodologies, periodically explore new technologies, introduce them to the machine learning community and promote their application in areas where they can generate impact. Actively contribute to Machine Learning at Booking.com through training, exploration of new technologies, interviewing,onboarding and mentoring colleagues. Push for improvements, scaling and extending machine learning tooling and infrastructure, collaborating with central teams. Qualifications & Skills: Strong programming skills in languages such as Python and Java. Experience with cloud frameworks like AWS sagemaker and training models using TensorFlow or PyTorch Experience with data at scale using MySQL, Pyspark, Snowflake and similar frameworks. Deep understanding of machine learning algorithms, statistical models, and data structures. Experience with experimental design, A/B testing, and evaluation metrics for ML models. Experience of working on products that impact a large customer base is an advantage Advanced knowledge and experience in Recommendation systems, including engineering aspects of developing ML models at scale is an advantage. Experience designing and executing end-to-end research and development plans and generating impact through large-scale machine learning model development. Preferably evidenced by peer-reviewed publication, patents, open sourced code or the like. Relevant work or academic experience (MSc + 5 years of working experience, or PhD + 3 years of working experience), involved in the application of Machine Learning to business problems. Experience on multiple machine learning facets: working with large data sets, model development, statistics, experimentation, data visualization, optimization, software development. Experience collaborating cross functionally in the development of machine learning products (e.g. Developers, UX specialists, Product Managers, etc.). Excellent English communication skills, both written and verbal. 3+ years leading an ML team of a minimum of 4 people in a fast-paced production environment. Successfully driving technical, business and people related initiatives that improve productivity, performance and quality while communicating with stakeholders at all levels Leading by example, gaining respect through actions, not your title. Developing your team and motivating them to achieve their goals. Providing feedback timely and managing your key team performance indicators Benefits & Perks - Global Impact, Personal Relevance: Booking.com’s Total Rewards Philosophy is not only about compensation but also about benefits. We offer a competitive compensation and benefits package, as well unique-to-Booking.com benefits which include: Annual paid time off and generous paid leave scheme including: parent, grandparent, bereavement, and care leave Hybrid working including flexible working arrangements, and up to 20 days per year working from abroad (home country) Industry leading product discounts - up to 1400 per year - for yourself, including automatic Genius Level 3 status and Booking.com wallet credit Diversity, Equity and Inclusion (DEI) at Booking.com: Diversity, Equity & Inclusion have been a core part of our company culture since day one. This ongoing journey starts with our very own employees, who represent over 140 nationalities and a wide range of ethnic and social backgrounds, genders and sexual orientations. Take it from our Chief People Officer, Paulo Pisano: “At Booking.com, the diversity of our people doesn’t just build an outstanding workplace, it also creates a better and more inclusive travel experience for everyone. Inclusion is at the heart of everything we do. It’s a place where you can make your mark and have a real impact in travel and tech.” We ensure that colleagues with disabilities are provided the adjustments and tools they need to participate in the job application and interview process, to perform crucial job functions, and to receive other benefits and privileges of employment. Application Process: Let’s go places together: How we Hire This role does not come with relocation assistance. Booking.com is proud to be an equal opportunity workplace and is an affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. We strive to move well beyond traditional equal opportunity and work to create an environment that allows everyone to thrive. 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.