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Expedia Group
Expedia Group

Online travel company

Data Scientist III - Product Analytics

직무데이터 사이언스
경력미들급
위치India - Bangalore; India - Gurgaon; IND0011 - Gurgaon - Downtown - Expedia
근무오피스 출근
고용정규직
게시1주 전
지원하기

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.

Introduction to the Team

The Product Team creates high-quality end-to-end experiences for travelers, partners, and Expedia Group. Our focus on customer-centric innovation enables us to develop products that build loyalty and repeat business. We partner closely with teams across Expedia Group to drive growth and achieve results for our customers and the company.

As a Data Scientist, you will help identify insights to improve the traveler experience and drive product growth. You will collaborate with a multi-disciplinary team on a wide range of problems. You will bring scientific rigor and statistical methods to the challenges of business growth and product development.

In this role, you will:

  • Design and execute complex experiments using advanced statistical methods, including A/B testing, causal inference, regression, and multivariate analysis

  • Apply supervised and unsupervised machine learning techniques to uncover insights, identify patterns, and support decision-making

  • Translate ambiguous business problems into structured analytical tasks, delivering clear and actionable insights

  • Partner cross-functionally with Product, Engineering, Risk, and Operations teams to influence strategy and execution

  • Build and maintain scalable analytics pipelines, automating repeatable analyses and processes where possible

  • Develop clear, engaging presentations, dashboards, and visualizations for both technical and non-technical audiences

  • Mentor junior team members and contribute to a culture of learning, collaboration, and analytical excellence

  • Leverage AI tools and emerging technologies to accelerate insight generation and improve analytical workflows

Experience and qualifications:

  • Bachelor’s or Master’s degree in Mathematics, Statistics, Computer Science, or a related field

  • 4+ years of professional experience in data science or analytics roles, preferably within travel, e-commerce, or fraud/risk domains

  • Strong proficiency in SQL, Python, and/or R, with hands-on experience using machine learning libraries and visualization tools (e.g., Plotly, Seaborn, ggplot)

  • Solid business acumen with the ability to connect data insights to real-world outcomes

  • Proven skills in storytelling, stakeholder management, and driving data-informed decisions

  • Demonstrated ability to lead analytical projects and influence outcomes across cross-functional teams

Note:

This job posting represents multiple openings within the team. Final role scope will be aligned based on the candidate’s experience, expertise, and interests.

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®, Cheap Tickets®, Expedia Group™ Media Solutions, Expedia Local Expert®, Car Rentals.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, religion, gender, sexual orientation, national origin, disability or age.

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Expedia Group 소개

Expedia Group

Expedia Group, Inc. is an American travel technology company that owns and operates travel fare aggregators and travel metasearch engines, including Expedia, Hotels.com, Vrbo, Travelocity, Hotwire.com, Orbitz, Ebookers, CheapTickets, CarRentals.com, Expedia Cruises, Wotif, and Trivago.

10,001+

직원 수

Seattle

본사 위치

$6.8B

기업 가치

리뷰

10개 리뷰

3.8

10개 리뷰

워라밸

2.8

보상

3.7

문화

4.2

커리어

3.3

경영진

2.5

68%

지인 추천률

장점

Supportive team and colleagues

Flexible work arrangements and remote options

Interesting and creative projects

단점

Work-life balance challenges and long hours

High stress and burnout during peak seasons

Fast-paced and overwhelming environment

연봉 정보

1개 데이터

Intern

Intern · Machine Learning Scientist Intern

1개 리포트

-

총 연봉

기본급

-

주식

-

보너스

-

면접 후기

후기 6개

난이도

2.8

/ 5

소요 기간

14-28주

면접 과정

1

Application Review

2

Recruiter Screen

3

Technical Assessment/Coding Challenge

4

Final Interview

5

Team Matching

6

Offer

자주 나오는 질문

Coding/Algorithm

Technical Knowledge

Behavioral/STAR

Past Experience

Culture Fit