This role is eligible for our hybrid work model: Two days in-office.

Our Data Science team is where smart solutions get created for the company. We build machine learning powered products that provide a core competitive edge over our competitors and they also contribute to the success of our business partners. We take pride in being excellent at our craft and employing our skills to the benefit of our customers. If you thrive in a fast-paced, ideas-led environment, you’re in the right place.

Why this job’s a big deal:

Have the opportunity to design new machine learning models and build new machine learning products in a small but growing team within a large organization. Work at a company where the business is increasing investment in Machine Learning solutions and sees the solutions as a competitive advantage. Solve real world problems that span various domains within our business such as: Price optimization, Sales forecasting, Hypothesis testing.

In this role you will get to:

1. Develop, productionize and maintain machine learning models on large, noisy datasets to solve business problems.
2. Research and design your own solutions.
3. Evaluate and improve existing machine learning models.
4. Work alongside data scientists and developers to integrate machine learning solutions into production platforms.
5. Understand business requirements from non-technical team members.
6. Present technical solutions to non-technical team members.
7. Utilize tools and libraries such as Python, Tensorflow, Keras, Spark, Numpy, Pandas, Spacy.
8. Train models using AWS Sagemaker and deploy services in Kubernetes.
9. Process large quantities of data streamed from many different applications to test and build models.

Who you are:

1. Masters or PhD qualification in a quantitative field such as Computer Science, Machine Learning / AI, Mathematics, Physics, Statistics, etc.
2. 8+ years of experience in machine learning, data science, or a related field.
3. Extensive experience in developing and deploying machine learning models in a production environment and data pipelines.
4. Proficiency in Python.
5. Strong understanding of machine learning algorithms, statistical methods, data preprocessing techniques and experiment design.
6. Experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, or scikit-learn.
7. Experience with cloud platforms (e.g., AWS, Google Cloud, Azure) and big data technologies (e.g., Spark).
8. Excellent communication and interpersonal skills.
9. Strong problem-solving and analytical abilities.
10. Ability to work effectively in a fast-paced, collaborative environment.
11. Strategic thinker with a passion for innovation and continuous learning.
12. Illustrated history of living the Priceline values: Customer-focus, Innovation, Team-orientation, Accountability, and Trust.
13. Experience with Pricing Modeling and/or Experience in the Hotel or B2B space preferred but not required.
14. Familiarity with AWS (Sagemaker, Athena, Lambda, IAM, EKS) preferred.
15. Unquestionable integrity and ethics is essential.