Machine Learning Scientist

Booking Holdings, Inc.; Amsterdam; Hybrid; EUR 110,000 - 170,000; Full time

Benefits offered by this job

Total Rewards

Hybrid working from abroad

Product discounts

Job summary

Booking.com, part of Booking Holdings, Inc., is seeking a Senior Machine Learning Scientist for the ABU ML team in Margin Management. You will design, build, and deploy uplift models and causal inference systems for promotional spend in the accommodation marketplace, validated through large-scale A/B experiments.

You will work on neural network architectures for structured data, publish applied research when possible, and collaborate with ML engineers, data scientists, product managers, and

Qualifications

• MSc or PhD in a quantitative field such as CS, Stats, Econ, OR, Math, or Physics.
• Experience applying ML to business problems (MSc+4 yrs or PhD+2 yrs).
• Strong knowledge in causal inference, uplift modeling, or treatment effect estimation.
• Proven end-to-end R&D planning and measurable impact through large-scale ML.
• Proficiency in Python and modern ML frameworks (TF, PyTorch).
• Experience with large-scale data systems and production ML pipelines (Spark, Airflow).
• Ability to collaborate cross-functionally with engineers, analysts, product managers, and stakeholders.
• Excellent English communication skills, written and verbal.

Responsibilities

• Design and deploy uplift models estimating heterogeneous treatment effects.
• Develop causal inference methodologies and offline/online evaluation.
• Advance neural architectures for uplift modeling on tabular data.
• Research marketplace interference and cannibalization and mitigation strategies.
• Develop offline evaluation methods predicting online performance.
• Own end-to-end ML models from research to production calibration.
• Collaborate with ML engineers, data scientists, product teams on ROI trade-offs.
• Mentor and guide junior team members on causal modeling practices.

Skills

Causal Inference

Uplift Modeling

A/B Testing

Python

TensorFlow/PyTorch

Production ML pipelines

Communication

Education

MSc in a quantitative field

PhD in a quantitative field

Tools

Spark

Airflow

LightGBM

XGBoost

Job description

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 make. The journeys you take. The sights you see. And the food you sample. Through our products, partners and people, we make it easier for everyone to experience the world.

About the team:

This opening is for the ABU ML team within Margin Management of the Accommodation Business Unit (ABU). The ABU ML team develops causal machine learning systems that power one of Booking.com’s biggest customer acquisition channels. We predict which promotional investments will drive genuinely incremental demand and deploy these models in production at scale. The work involves uplift modeling, causal inference under marketplace interference, neural network design for structured data, and rigorous online experimentation. The team actively contributes to the research community, our recent work “Converted Data is All You Need for Causal Optimization of e-Commerce Promotions” was published at ACM CIKM 2025. We encourage publishing and conference participation when the work advances the state of the art.

As a Senior Machine Learning Scientist, you will design, build, and deploy uplift models and causal inference systems that allocate promotional spend across Booking.com’s accommodation marketplace. The role combines causal methodology, neural network architecture design, and production ML — with your work validated through large-scale A/B experiments. There are opportunities to publish applied research at top venues when the work contributes novel methodology.

Key Job Responsibilities and Duties:

• Design and deploy uplift models that estimate heterogeneous treatment effects, optimising incremental return on investment under budget constraints.

• Design and execute causal inference methodologies; including observational debiasing (IPW, doubly robust estimation), sensitivity analysis, and interference-aware evaluation to close the gap between offline metrics and online impact.

• Advance the team’s neural network architectures for uplift modeling on tabular data (attention mechanisms, multi-head designs, self-supervised pretraining), balancing model expressiveness with production latency requirements.

• Research marketplace interference and cannibalization; building frameworks to measure and correct for demand shifting when partial treatment is applied across competing properties.

• Develop offline evaluation methods that reliably predict online performance, accounting for biases introduced by non-stationary treatment policies and interference effects.

• Own models end-to-end; from research through A/B experimentation to production calibration.

• Collaborate cross-functionally with ML engineers on pipeline and serving design, with data scientists on feature engineering, and with product and business stakeholders on spend strategy and ROI trade-offs.

• Actively coach and mentor less experienced team members, setting technical direction and providing guidance on causal modeling best practices.

Role Qualifications and Requirements:

• MSc or PhD (or equivalent experience) in a quantitative field such as Computer Science, Statistics, Economics, Econometrics, Operations Research, Mathematics, or Physics.

• Relevant professional or academic experience applying Machine Learning to business problems (typically MSc + 4 years, or PhD + 2 years).

• Advanced knowledge and experience in Causal Inference, Uplift Modeling, or Treatment Effect Estimation. Experience with heterogeneous treatment effects, interference / spillover effects, or policy learning is highly valued.

• Proven track record designing and executing end-to-end R&D plans, and generating measurable impact through large-scale ML model development. Evidence such as peer-reviewed publications, patents, or open-source contributions is a plus.

• Strong proficiency in Python and modern ML frameworks (e.g., TensorFlow, PyTorch, LightGBM, XGBoost).

• Solid understanding of experimental design, A/B testing, and statistical methodology — including awareness of SUTVA violations, selection bias, and observational study limitations.

• Experience working with large‑scale data systems and production ML pipelines (Spark, Airflow, or similar).

• Experience with neural network design for structured/tabular data (embeddings, attention, multi-task architectures) is a strong plus.

• Experience collaborating cross-functionally with developers, analysts, product managers, and other scientists to deliver ML-powered products.

• Excellent English communication skills, both written and verbal. Ability to communicate complex causal reasoning clearly to both technical and non-technical audiences.

• Successfully driving technical initiatives and cross-team collaboration while communicating with stakeholders at all levels.

Benefits & Perks - Global Impact, Personal Relevance:

Booking.com’s Total Rewards Philosophy is not only about compensation but also about benefits. We offer a competitivecompensation 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

Inclusion at Booking.com:

Take it from our Chief People Officer, Paulo Pisano: “At Booking.com, the diversity of our people doesn’t just create a unique 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.”

Read all about Inclusion and the Employee Resource Groups (ERGs) at Booking.com here.

Career Development Opportunities

• Learn more aboutYour Career Journeyhere.

• Become a Menteeand benefit from a mentoring relationship with a more experienced person to help you identify and achieve your professional and personal development goals.

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.