About the role:
As a machine learning scientist, your work will focus on building, training and deploying promotional targeting models (Causal Inference, Uplift Modeling, Optimization, 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 build the Value Intelligence Platform, contributing in engineering and analytics efforts.
Key Job Responsibilities and Duties:
- Build, train and deploy state-of-the-art machine learning techniques in causal inference, uplift modeling and active learning to effectively optimize promotional campaigns at Booking and drive clear business value.
- Contribute in engineering and analytics efforts to improve the way we analyze and optimize promotional campaigns through the Value Intelligence Platform.
- Ensure implementation of reusable frameworks (clean and scalable code).
- Conduct data analysis with detailed metrics to improve data quality, do feature exploration, evaluate model’s performance, etc.
- Work closely with Machine Learning Engineers to ensure the models meet product and engineering requirements and ensure deployment of your model to production.
- Collaborate with multidisciplinary teams: Collaborate with product managers, engineers, data scientists and data analysts to understand business requirements and translate them into machine learning solutions.
Role Qualifications and Requirements:
We have found that people who match the following requirements are the ones who fit us best:
- Advanced knowledge and experience in Causal Inference, Uplift Modeling, Active Learning, Reinforcement Learning and/or Optimization.
- 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.
- Experience in data analytics, experimentation, A/B testing and statistics.
- 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.
- Masters degree, PhD or equivalent experience in a quantitative field (e.g. Computer Science, Engineering, Mathematics, Artificial Intelligence, Physics, etc.).
- 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.).
- Strong working knowledge of Python,, Kafka, Hadoop, SQL, and Spark or similar technologies. Working experience with version control systems.
- Excellent English communication skills, both written and verbal.
- 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
Booking.com’s Total Rewards Philosophy is not only about compensation but also about benefits. Our Total Rewards strive to make it easier for you to experience all that life has to offer on your terms so that you can focus on what really matters. We offer competitive compensation as well as thoughtful, valuable, and even fun benefits which include:
- Headquarters located in one of the most dynamic and cosmopolitan cities in Europe: Amsterdam.
- Contribute to a high scale, sophisticated, world-class product and see the real time impact of your work on millions of travelers worldwide.
- Be part of a truly international fast paced environment and performance driven culture.
- Performance-based company that offers career advancement, and lucrative compensation, including bonuses and stock potential.
- Discount on Booking.com accommodations with the “Booking Deal” including other perks and benefits.
- Company-sponsored family and social activities to help our employees become integrated with each other and the company's culture.
- Diverse and creative colleagues from every corner of the world.
- Health, life, and disability insurance*
- 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 for yourself, friends, and family, including automatic Genius Level 3 status and quarterly Booking.com wallet credit.
- Free access to online learning platforms, development and mentorship programs, and a complimentary Headspace membership
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.
