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Machine Learning Scientist - Performance marketing (PPC)

View all Jobs from Booking.com
Location
Manchester, Greater Manchester, United Kingdom
Salary
TBD
Job type
Full Time
Category
Other
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As a Machine Learning Scientist you are a subject-matter expert in the theory behind one or more of the following areas of machine intelligence: recommendation systems, classification/regression problems, neural networks, gradient boosting, and 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 ideation to prototyping to full productionisation.

At PPC Bidding, which is part of Booking's Marketing department, we are developing bidding strategies to manage Booking's online search advertising budget (one of the largest online advertising budgets in the world).

We are developing machine learning models to ensure we efficiently display Booking ads to the right customers depending on their search intent. From predicting a customer's probability to convert to optimizing marketplace strategy in the competitive space of the digital travel industry, we value innovation, ownership and a result-driven attitude.

Responsibilities
  • Develop the strategy and research plan for machine intelligence 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.
  • Document and share the findings, and generalise these technologies into reusable frameworks.
  • Translate broad business problems into ML/AI challenges and identify the best approach within the constraints of the production environment.
  • Independently define and build proof-of-concepts to test new ideas and demonstrate their potential value to relevant stakeholders.
  • Drive the end-to-end execution of the ML/AI development process on products, from understanding product requirements, data discovery, model development and evaluation, to implementation of a full production pipeline for both batch and stream-based deployment.
  • Develop production-grade machine learning code, from models to features and pipelines, allowing for scalability, realtime, monitoring and retraining.
  • Monitor product health, performance and business impact and act accordingly when requirements are not met.
  • Build readable and reusable code, choosing the right technologies, coding methodologies, and approach from carefully designed rapid prototyping to software deployment at scale.
  • 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.
  • Identify underlying issues and opportunities across domains and situations through application of structured thinking and logic, and drive concrete improvements. Guide and support colleagues dealing with complex scenarios.
  • 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.
  • Push for improvements, scaling and extending machine learning tooling and infrastructure, collaborating with central teams.

Your skills and experience
  • Ability to design an applied research plan for a product family from scratch as evidenced by peer-review publication or similar track record.
  • Strong relevant work or academic experience (MSc + 3 years of working experience, or PhD), 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).
  • 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, Hadoop, SQL, Spark or similar big data technologies.
  • Experience working with GCP environment and Airflow
  • Excellent English communication skills, both written and verbal.

What do we offer?
  • Contributing to a high scale, complex, world-class product and seeing real-time impact of your work on millions of travelers worldwide
  • Working in a fast-paced, pragmatic and performance driven culture
  • Opportunity to apply your 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
  • Hybrid working

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.
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