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.
About the team:
The Financial Planning & Analysis team acts as the analytical engine of the finance organization, providing critical insights and recommendations that shape a company’s financial health and strategic direction. As a Machine Learning Scientist, you will be part of the “Forecast of the Future” program which will be responsible for implementing ML based statistical forecasting models at the core of our financial forecasting & budgeting process, with the aim to make our forecasts more agile, accurate, scenario-based and connected (driver-based and multi-vertical).
Role Description:
We are seeking an experienced Machine Learning Scientist to join our Financial Planning & Analysis (FP&A) team, focusing on advanced forecasting initiatives. In this role, you will design, develop, deploy, and maintain machine learning solutions—primarily in the areas of time series forecasting and regression modeling—to drive data-driven financial planning and decision-making. You will collaborate with business stakeholders to identify key features for enhancing forecasting accuracy. You will also be responsible for feature exploration and conducting successful experiments to guide the company toward driver-focused forecasting.
Key Job Responsibilities and Duties:
- Work in a multi-disciplined, highly skilled team where you will be developing, implementing, and optimizing time series forecasting and regression models for financial planning, budgeting, and scenario analysis
- Collaborate with FP&A analysts, data scientists, and business stakeholders to understand forecasting requirements and translate them into scalable ML solutions.
- Leverage AWS SageMaker for model development, training, deployment, and lifecycle management, including use of Data Wrangler, Model Registry and Feature Store
- Monitor model performance, detect model drift, and implement retraining strategies to maintain accuracy and relevance over time
- Conduct data analysis with detailed metrics to improve data quality, do feature exploration, evaluate model’s performance, etc.
- Ensure data quality, feature engineering, and preprocessing of large, complex financial datasets
- Drive a culture of quality for all ML practitioners, maintain data security, integrity and quality, and make choices over the right technologies and coding methodologies
- Identify underlying issues and opportunities across the ML development cycle and introduce tools to be used within and outside the team for efficient development and testing
- Continuously evolve your craft, keeping up to date with the latest technologies
- Collaborate with relevant ML teams across the company to improve, scale and extend machine learning tooling and infrastructure
Qualifications and Skills:
- Bachelor’s or Master’s degree in Computer Science, Engineering, Statistics, Mathematics, or a related field
- 3+ years of relevant work experience, involved with the application of Machine Learning algorithms & statistical forecasting to business problems in a commercial environment
- Strong skills in coding and problem solving. Proficiency in at least one programming language; preferably Python and strong command of SQL is strictly required. Knowledge of Snowflake is a plus
- Proven experience building and deploying forecasting models (time series, regression) in a financial or business analytics context
- Experience running Machine Learning systems in production is a must, with knowledge on how to generate predictions for ML frameworks with high throughput
- Solid understanding of cloud platforms, containerization, and version control (e.g., Docker, Git)
- Demonstrable experience of multiple machine learning facets, such as working with large data sets, experimentation, scalability and optimization
- Proficiency in Airflow & AWS SageMaker for end-to-end ML workflows is a plus
- Familiarity with additional AWS services (e.g., Lambda, ECS, CloudWatch) and infrastructure-as-code tools is a plus
- Willingness to learn and understand complex and multidisciplinary business problems and concepts related to booking.com business operations especially in finance
- You have a ‘can do’ attitude and you act proactively and not reactively
- Excellent English communication skills, both written and verbal
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
- Living and working in Amsterdam, one of the most cosmopolitan cities in Europe
- Contributing to a high scale, complex, world renowned product and seeing real-time impact of your work on millions of travelers worldwide
- Working in a fast-paced and performance driven culture
- Opportunity to utilize technical expertise, leadership capabilities and entrepreneurial spirit
- Promote and drive impactful and innovative engineering solutions
- Technical, behavioral and interpersonal competence advancement via on-the-job opportunities, experimental projects, hackathons, conferences and active community participation
- Competitive compensation and benefits package and some great added perks of working in the home city of Booking.com
Inclusion at Booking.com:
Inclusion has 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.
