Introduction to team

Private Label Solutions (PLS) is the B2B arm of Expedia Group. We open up our supply and innovative technology to businesses looking to take on the world of travel. These businesses, sometimes referred to as our ‘demand partners’, include global financial institutions (e.g. AMEX), corporate managed travel, offline travel agents (e.g. Flight Centre), global travel suppliers (e.g. Delta) and many more.

The Data Scientist III - Revenue Optimization Analytics role is vital to the Analytics team supporting Revenue Optimization initiatives in PLS. This team leverages advanced analytics capabilities, best practices, and processes to address complex business challenges and identify revenue opportunities. As a high-performing individual contributor, you will consistently apply and enhance these analytics capabilities to drive impactful solutions. In this role, your expertise in data-driven decision-making, along with your ability to operate largely independently and mentor junior colleagues, will significantly enhance revenue performance and optimize business strategies across the organization. We are an analytics function, and as such, we are the bridge between our Machine Learning Science and Engineering teams and senior commercial stakeholders (VPs and C-suite).

The Data Scientist III - Revenue Optimization Analytics - Experimentation role is vital to the Analytics team supporting Revenue Optimization initiatives in PLS. This team leverages advanced analytics capabilities, best practices, and processes to address complex business challenges and identify revenue opportunities. As a high-performing individual contributor, you will consistently apply and enhance these analytics capabilities to drive impactful solutions. In this role, your expertise in data-driven decision-making, along with your ability to operate largely independently and mentor junior colleagues, will significantly enhance revenue performance and optimize business strategies across the organization. We are an analytics function, and as such, we are the bridge between our Machine Learning Science and Engineering teams and senior commercial stakeholders (VPs and C-suite).

In this role, you will:

• Apply statistical, probabilistic and ML knowledge to measure the impact of our algorithms and models.

• Propose new or alternate solutions to enhance our capabilities.

• Measure the performance of commercial actions.

• Mathematical modelling of market reactions to our commercial actions.

• Work with big data, navigating potential challenges and providing explanations to both technical and non-technical partners with minimal guidance

• Frame complex business problems as analytical tasks, breaking them down into manageable chunks.

• Apply machine learning techniques to relevant projects, validating and scaling models for optimal business value.

• Mentor junior colleagues.

Experience and qualifications:

Education

PhD with 2+ years of experience, Master's or Bachelor’s degree with 4+ years of experience (in quantitative fields such as Mathematics, Physics, Statistics, Computer Science, Economics, etc).

Functional/ Technical Skills

• Demonstrable advanced-level experience in using SQL and fluency in Python (R and no-SQL nice to have).

• Experience with Pyspark.

• Experience applying Probability and Statistics in business settings.

• Real-world experience with AB testing (including design of tests).

• Problem solving.

• Critical thinking.

• Business acumen.

• Experience measuring the performance of Revenue Optimization or bidding algorithms.

• Machine learning concepts/approaches.