Senior Machine Learning Scientist - Applied Payments

Senior Machine Learning Scientist – Applied Payments

United States - Washington - Seattle

Technology

Full-Time Regular

10 / 10 / 2025

ID # R-97676

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.

Why Join Us?

To shape the future of travel, people must come first. Guided by our Values and Leadership Agreements, we foster an open culture where everyone belongs, differences are celebrated and know that when one of us wins, we all win.

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.

The Technology Team at Expedia Group partners with our Product teams to create innovative products, services, and tools to deliver high-quality experiences for travelers, partners, and our employees. A singular technology platform powered by data and machine learning provides secure, differentiated, and personalized experiences that drive loyalty and traveler satisfaction.

Introduction to the Team :

Payments at Expedia Group sits at the intersection of trust, conversion, and global scale. Every millisecond counts and every decision impacts traveler experience, authorization rates, cost to serve, and platform reliability. As our Senior Machine Learning Scientist for Payments, you’ll be the technical lead bringing practical, high‑impact ML to a complex, high‑volume domain—turning ambiguous business problems into scalable solutions that quietly power millions of secure transactions worldwide.

If you’re excited by ownership, product thinking, and making ML work in production (not just on paper), this is where you’ll have outsized impact.

In this role, you will :

Lead ML for Payments : Serve as the technical lead for a small, focused ML group supporting Payments. Set the roadmap, shape best practices, and mentor 1–2 scientists / engineers in the area.

Partner deeply with Product & Payments Engineering : Co‑define problems, discover hidden ML opportunities, and align on KPIs (e.g., authorization and approval rates, false decline reduction, latency / SLA adherence, cost optimization, partner routing quality).

Ship production models end to end : Own problem framing, data exploration, feature engineering, model selection, training / validation, offline / online evaluation, deployment, and ongoing monitoring.

Focus on the right tools for the job : Apply binary classification, anomaly detection, and multi‑armed bandits where they provide clear measurable value; avoid over‑engineering.

Elevate reliability & safety : Implement robust monitoring (drift, stability, performance, fairness), incident playbooks, and model lifecycle hygiene (versioning, rollback, reproducibility).

Tell the data story : Communicate findings and trade‑offs to technical and non‑technical stakeholders; influence priorities with clear narratives and evidence.

Raise the bar : Contribute to ML standards, reusable features, and internal communities of practice across EG.

Minimum Qualifications :

Bachelor\'s, Master\'s, or PhD in Computer Science, Statistics, Engineering, or a related technical field; or Equivalent related professional experience.

7+ years (with a Bachelor\'s), 5+ years (with a Master\'s), or 4+ years (with a PhD) of professional experience in data science or machine learning roles.

Proficient coding skills in Python or Scala, with experience writing clean, maintainable, and optimized ML code.

Deep understanding of supervised learning, anomaly detection, and model evaluation techniques.

Experience deploying ML models in production environments.

Proven ability to translate ambiguous business problems into actionable ML solutions.

Proficient communication and stakeholder management skills.

Preferred Qualifications :

Experience in payments or financial systems, with an understanding of the domain\'s complexity.

Familiarity with multi‑armed bandits, anomaly detection, and binary classification models.

Experience leading ML initiatives with a product‑focused mindset and cross‑functional collaboration.

Exposure to cloud‑based ML infrastructure and data pipelines (e.g., AWS, GCP, Azure).

Contributions to technical communities (e.g., publications, open‑source projects, tech talks).

Strong business acumen and ability to connect ML outcomes to strategic goals.

Expedia Group is proud to offer a wide range of benefits to support employees and their families, including medical / dental / vision, paid time off, and an Employee Assistance Program. To fuel each employee’s passion for travel, we offer a wellness & travel reimbursement, travel discounts, and an International Airlines Travel Agent (IATAN) membership. View our full list of benefits.

The total cash range for this position in Seattle is $173,000.00 to $242,500.00. Employees in this role have the potential to increase their pay up to $277,000.00, which is the top of the range, based on ongoing, demonstrated, and sustained performance in the role.

Starting pay for this role will vary based on multiple factors, including location, available budget, and an individual’s knowledge, skills, and experience. Pay ranges may be modified in the future.

Expedia Group is proud to offer a wide range of benefits to support employees and their families, including medical / dental / vision, paid time off, and an Employee Assistance Program. To fuel each employee’s passion for travel, we offer a wellness & travel reimbursement, travel discounts, and an International Airlines Travel Agent (IATAN) membership. View our full list of benefits.

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.

Expedia Group\'s family of brands includes : Brand Expedia®, Hotels.com®, Expedia® Partner Solutions, Vrbo®, trivago®, Orbitz®, Travelocity®, Hotwire®, Wotif®, ebookers®, CheapTickets®, Expedia Group™ Media Solutions, Expedia Local Expert®, CarRentals.com™, and Expedia Cruises™. © 2024 Expedia, Inc. All rights reserved. Trademarks and logos are the property of their respective owners. CST : 2029030-50

Employment opportunities and job offers at Expedia Group will always come from Expedia Group’s Talent Acquisition and hiring teams. Never provide sensitive, personal information to someone unless you’re confident who the recipient is. Expedia Group does not extend job offers via email or any other messaging tools to individuals with whom we have not made prior contact. Our email domain is @expediagroup.com. The official website to find and apply for job openings at Expedia Group is careers.expediagroup.com / jobs.

Expedia is committed to creating an inclusive work environment with a diverse workforce. 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. This employer participates in E-Verify. The employer will provide the Social Security Administration (SSA) and, if necessary, the Department of Homeland Security (DHS) with information from each new employee\'s I-9 to confirm work authorization.

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