Machine Learning Scientist II, Search Marketing Bidding

Expedia Group brands power global travel for everyone, everywhere. We design cutting-edge tech to make travel smoother and more memorable, and we create groundbreaking solutions for our partners. Our diverse, vibrant, and welcoming community is essential in driving our success.

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We provide a full benefits package, including exciting travel perks, generous time-off, parental leave, a flexible work model (with some pretty cool offices), and career development resources, all to fuel our employees' passion for travel and ensure a rewarding career journey. We’re building a more open world. Join us.

Machine Learning Scientist II, Search Marketing Bidding

Introduction to team:

The Search Product & Optimization team at Expedia Group sits within the Marketing division and is responsible for the algorithmic intelligence behind our global marketing investments. We operate in a fast-paced and dynamic environment, participating in millions of auctions daily across Search, Metasearch and Social platforms.

Our mission is to build scalable, data-driven systems that optimize how we acquire traffic. We are moving beyond traditional analytics to develop automated decisioning systems that dynamically allocate investment to maximize business value. We operate under a build & scale philosophy, creating solutions that adapt to a rapidly evolving search marketing landscape.

As a Machine Learning Scientist II, you will sit at the intersection of Data Science, Engineering and Marketing Management. You will work within a cross-functional squad to design, build and deploy machine learning models that solve complex investment allocation problems.

You will focus on understanding the relationship between marketing cost and incremental financial returns, building algorithms that help us bid efficiently and effectively in competitive marketplaces. You will move beyond offline analysis to build production-grade models that drive real-world actions.

In this role, you will:

• Design and implement machine learning models to optimize bidding strategies (e.g., Cost-Per-Click, Target ROAS, Target CPA) and investment allocation across diverse marketing channels.

• Develop methodologies to measure elasticity (how performance changes as spend scales) to help us answer granular capital allocation questions.

• Write clean, efficient and reproducible Python code. You will partner with Machine Learning Engineers to deploy your models into production environments, ensuring they are robust and scalable.

• Contribute to the development of feedback loops and control mechanisms that allow our bidding systems to self-correct and adapt to market volatility or competitor changes.

• Design and analyze A/B experiments to validate model performance and inform strategic decisions.

• Translate mathematical concepts into clear insights for business partners. You will help frame vague business problems into concrete analytical tasks and define the objective functions that our models solve for.

Experience & Qualifications:

• Bachelor or Master’s degree in a quantitative field (Computer Science, Statistics, Mathematics, etc.) or equivalent practical experience.

• 2+ years of professional experience applying Machine Learning to real-world business problems.

• Strong Python proficiency in writing production-quality code and using libraries like pandas, scikit-learn, numpy.

• Advanced SQL ability to write complex queries to handle large-scale datasets.

• Solid understanding of regression (GLMs), optimization techniques, time-series forecasting and probability theory.

• A strong interest in AdTech, Bidding Markets, Game Theory, or Control Systems. You are curious about how auctions work and how to optimize within them.

• Comfortable working with ambiguity. You can take a high-level goal and break it down into a solvable mathematical problem.

Accommodation requests

If you need assistance with any part of the application or recruiting process due to a disability, or other physical or mental health conditions, please reach out to our Recruiting Accommodations Team through the Accommodation Request.

We are proud to be named as a Best Place to Work on Glassdoor in 2024 and be recognized for award-winning culture by organizations like Forbes, TIME, Disability:IN, and others.

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