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Senior Machine Learning Scientist - Customer centric data

Booking.com

Booking.com

Software Engineering, Customer Service
Amsterdam, Netherlands
Posted on Saturday, April 20, 2024

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.

Team and Role Overview

Ensuring we understand the needs and intentions of our travelers remains a top priority for Booking. With millions of accommodations, flights, taxis, attractions, and car rentals available on our platform, our aim is to assist customers in finding the perfect fit for their journey. Customers may express their needs and intentions directly through their searches or filter usage, while in addition we can further deduct their preferences from their interactions on our platform, such as clicking on specific accommodations rather than others. At Booking, we consistently analyze and model customer behavior to personalize the traveler experience.

Following successful user intent and needs modeling across various parts of the company, these efforts have recently been consolidated into a central team, and as part of the Traveler Centric Data track within the new Marketplace business unit we are now expanding further. The User Intent Modelling team is building upon past successes, while also deepening on innovation to push the boundaries for personalisation even further by leveraging innovative Machine Learning and Artificial Intelligence. It is a crucial aspect of the Marketplace vision to ensure we guide our travelers to the most suitable products and facilitate seamless connections between the various parts of their trip.

As a Senior Machine Learning Scientist, you will be a strong technical leader within the team, setting the technical strategy, while generating operational business impact. You will be developing state-of-the-art Machine Learning models, owning the design and delivery of ML systems, from initial idea-generation, collecting business requirements from product stakeholders to implementation. You will actively coach and mentor less experienced Machine Learning Scientists and Machine Learning Engineers in the team and work closely together with Data Engineers, Software Engineers and Product Managers.

Key Job Responsibilities

  • Translate broad business problems into ML/AI challenges and develop a targeted research plan to identify the best approach within the constraints of the production environment.
  • Develop the technical strategy for machine learning on a product family by designing innovative ML/AI models, algorithms, and approaches that deliver both short-term commercial impact and longer-term differentiated business value and customer experiences.
  • Work in a multi-disciplined team where you’ll take full ownership of turning discoveries and ideas into products through machine learning (incl. understanding product requirements, data discovery, model development and evaluation, to implementation of a full production pipeline for both batch and stream-based deployment).
  • Define and build proof-of-concepts to test new ideas and demonstrate their potential value to relevant stakeholders.
  • Develop production-grade ML code for models, features, and pipelines, accounting for scalability, latency, realtime requirements, monitoring and retraining.
  • Build readable and reusable code, using the right technologies and coding methodologies applying knowledge of business area tools and product needs.
  • Continuously evolve your craft by keeping up to date with the latest developments in ML/AI and related technologies, introducing them to the machine learning community and promoting their application.
  • Promote platform-based development and reuse by coaching teams in abstracting individual business problems to generalized ML/AI products, rather than point solutions, and in identifying horizontal opportunities across multiple business domains.
  • Maintain a highly cross-disciplinary perspective, solving issues by applying approaches and methods from across a variety of ML/AI disciplines and related fields. Coach others through evidence and clear communication, explaining advanced technical concepts in simpler terms.
  • Actively contribute to Machine Learning at Booking.com through training, exploration of new technologies, interviewing, onboarding and mentoring colleagues.

Role Qualifications and Required Skills

  • Strong relevant work and/or academic experience (MSc + 8 years of working experience, or PhD + 6 years), involved in the development and application of Machine Learning.
  • Masters degree, PhD or equivalent experience in a quantitative field (e.g. Computer Science, Mathematics, Artificial Intelligence, Physics, etc.).
  • We prefer candidates with Deep Learning experience, especially when applied to large-scale datasets. Experience with TensorFlow is a plus.
  • Ability to design an applied research plan for a product family from scratch as evidenced by peer-review publication or similar track record.
  • Experience on multiple machine learning facets: working with large data sets, model development, statistics, experimentation, data visualization, optimization, software development.
  • Prior experience with Feature Engineering and putting machine learning models in production is a plus.
  • Strong working knowledge of Python, Hadoop, SQL, Spark or similar Big Data technologies.
  • Experience collaborating cross functionally in the development of machine learning products (e.g. Developers, ML Engineers, Product Managers, etc.).
  • Excellent English communication skills, both written and verbal; the ability to convey your message to team members and other collaborators.

Benefits & Perks: Global Impact, Personal Relevance

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.
  • Full relocation support for you and your family to move to Amsterdam. We have fine-tuned this process by successfully relocating over 300 Technology professionals to Amsterdam in the last year alone!
  • Performance-based company that offers 29 vacation days, 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 Dutch 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.
  • On-site meals, coffee, and snacks, including healthy and vegan options, daily*

DEI: Diversity, Equity and Inclusion at Booking.com

Inclusion, Diversity, Belonging, Wellbeing and Volunteering (IDBWV) 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 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.”

We will ensure that individuals with disabilities are provided reasonable adjustment to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment.

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.

Career Development Opportunities

  • Bi-annual performance conversations, company-wide mentoring program, and internal development opportunities
  • Unlimited access to online learning platforms: Udemy, Coursera, LinkedIn learning, O'reilly

Application Process

The interview process will entail: an initial screen by one of our Recruiters, and a total of 3 Business interviews (including a take home business case).

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.