Machine Learning Scientist - Cars

Machine Learning Scientist - Cars

Job description

We began by taking hotel bookings online over 20 years ago and we've been shaping the travel industry ever since. Today, we're building a platform that connects all parts of the trip from accommodation to transport, flights, tickets, tours and much more!

From our hubs in Manchester, London, Amsterdam our Trips Business Unit helps people get where they want to go, anywhere in the world.

Whether customers want the freedom of a car, the convenience of a flight, the ease of a taxi or the economy of public transport, we make it all possible.

Our team is passionate about helping people travel. They see challenges as opportunities. And they’re always ready for change.







Booking.com is the world's largest car rental platform featuring car rental in more than 60'000 locations in 160 countries.

Our product is available to our global customer base via desktop, mobile and app and under 2 consumer brands : Booking.com and Rentalcars.

com, our dedicated car rental platform. In addition to our consumer brands we also power the car rental business for our many affiliate partners including some of the world's leading airlines and online travel agencies.

Role Description :

We are looking for a Mid-level Machine Learning Scientist to join our Cars Vertical. As a successful candidate, you will working closely with the Search Product Teams.

We will iteratively optimize our product to enable our users to find the best Cars at the most relevant location using a combination of ML techniques, engineering, online experimentation, and agile product development.

You will work across the full ML lifecycle and bring your models to production and make sure they help our users,





communicating findings and contributing knowledge to the insights and data community at Booking.

You'll be part of a wider team of Data Scientists, Machine Learning Scientists, and Data Analysts, who cover a wide spectrum of topics within the Trips area.

Our recent work revolves around Ranking, Pricing and Recommendation Models. At the same time you will be embedded in a product development team, working side-by-side with Product and Engineering, to create the optimal experience for our customers.

As an MLS you are a subject-matter expert in the theory behind relevant areas of machine intelligence, such as recommendation systems, ranking, multi-arm bandits, uplift modeling, or classification / regression techniques, and in their implementation as end-to-end products that generate direct business impact.







You define the strategy and vision for how to generate outsized impact through automated intelligence for a product by driving a research agenda and development plan from conceptualisation to prototyping to full production.

Key Job Responsibilities and Duties :

- Translate broad business problems into ML / AI challenges. Develop the approach to solving them 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.
- Drive the end-to-end execution of the ML / AI development process on products, from understanding product requirements and constraints of the production environment, data discovery,





proof-of-concept demonstrations, model development and evaluation, to implementation of a full production pipeline, and their monitoring.
- Develop production-grade machine learning code, from models to features and pipelines, allowing for scalability, realtime, monitoring and retraining.
- Maintain a highly cross-disciplinary perspective, solving issues by applying approaches and methods from across a variety of ML / AI subject areas and related fields.
- 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 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.

Champion improvements, scaling and extending machine learning tooling and infrastructure, collaborating with central teams.

Role Qualifications and Requirements :

- Strong relevant industry experience involved in the development and application of Machine Learning in a commercial environment
- Masters degree, PhD or equivalent experience in a quantitative field (e.g. Computer Science, 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 with different teams and crafts (e.g. Developers, UX specialists, Product Managers, etc).
- Ability to break down complex problems into smaller iterative tasks
- Strong working knowledge of Python, Hadoop, SQL, Spark or similar data technologies.
- Excellent English communication skills, both written and verbal.

Benefits & Perks :

Booking.com’s Total Rewards Philosophy is not only about compensation but also about benefits. Our Total Rewards are aimed to make it easier for you to experience all that life has to offer all the messy, beautiful, and joyful bits on your terms.

So you can focus on what really matters. We offer competitive compensation as well as thoughtful, valuable, and even fun benefits which include :

- 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*
- Please note that while our philosophy is the same in every location, benefits may differ by office / country.





More details on the benefits and perks offered by the company can be found here.

ThinkInclusion : Wellbeing & Inclusion at Booking.com :

Directly linked to our mission to make it easier for everyone to experience the world, 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.

Our DBWV overview can be found here.

Application Process :

Learn more here about what to expect in our interview process : Your Journey

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.

▶️ Machine Learning Scientist - Cars
🖊️ Booking.Com
📍 Manchester