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职位Expedia Group

Data Scientist III, Product Analytics

Expedia Group

Data Scientist III, Product Analytics

Expedia Group

India - Bangalore; India - Gurgaon

·

On-site

·

Full-time

·

2w ago

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.

We are looking for a Data Scientist III, Product Analytics to partner closely with product, design, and engineering to drive decisions across our membership and loyalty experiences. This is an established IC role that independently owns analytics for one or more product areas, applying strong product thinking, experimentation, and storytelling skills with a moderate level of guidance.The role regularly interacts with stakeholders up to Senior Director level and is expected to influence strategy through clear, data‑backed recommendations.

In this role, you will:

  • Partner with product teams to clarify business problems, define success metrics, and translate ambiguous questions into structured analytical plans.

  • Design, run, and analyze experiments (A/B tests, pre/post, quasi‑experimental reads) to measure impact, quantify trade‑offs, and guide iteration.

  • Perform deep‑dive product analysis (funnels, cohorts, segmentation, sizing) to uncover drivers of performance and identify opportunities for growth and customer experience improvements.

  • Build reliable datasets and dashboards using SQL and modern BI tools, enabling self‑serve product performance monitoring across platforms (web, app, partner).

  • Apply solid statistical thinking (probability, sampling, inference, regression) to ensure reads are robust, distinguish signal from noise, and clearly communicate caveats.

  • Use Python/R (or similar) to prototype models and advanced analyses when needed (e.g., regression, clustering, simple prediction) and to automate recurring analytics workflows.

  • Tell clear, compelling stories that move stakeholders from insight to action—framing context, methods, results, and recommendations for both technical and non‑technical audiences.

  • Champion data quality and reproducibility by following best practices for data validation, query performance, version control, and documentation.

  • Collaborate and upskill others by seeking peer review, sharing best practices, and providing light mentorship to more junior analysts or data scientists.

Experience and qualifications:

  • 5+ years of experience in analytics, product analytics, or data science roles.

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

  • Proven track record of delivering data‑driven insights and recommendations that influenced product decisions or drove measurable performance improvements.

  • Strong SQL: able to work confidently with large, complex datasets; write intermediate queries (joins, subqueries, CASE logic, window functions, unions); and optimize for performance and cost.

  • Experience with at least one scripting language such as Python or R for analysis, modeling, and automating recurring tasks.

  • Experimentation and statistics: comfortable with hypothesis testing, confidence intervals, experiment design, and interpreting regression/logistic regression outputs.

  • Hands‑on experience with A/B testing platforms and understanding of when to use experiments vs. observational or exploratory analysis.

  • Data visualization and dashboarding skills (e.g., Tableau, Power BI, or similar) with a focus on clarity, appropriate chart selection, and inclusive design basics (e.g., color use, accessibility).

  • Ability to build and validate basic models (e.g., linear/logistic regression, simple clustering) and understand data/feature requirements and key assumptions.

  • Demonstrated product sense: ability to connect metrics to customer journeys, refine problem statements, and propose pragmatic analytical approaches aligned with business timelines.

  • Experience defining or refining product KPIs, building scorecards, and monitoring performance for ongoing features and launches.

  • Strong critical thinking and problem‑solving skills; able to break complex problems into manageable analytical steps and iterate based on learnings.

  • Excellent communication and influencing skills—comfortable presenting to PMs, engineers, designers, and senior leaders, and adapting depth/rigor to the audience.

  • Collaborative working style, with a proactive, ownership‑oriented mindset and openness to feedback, peer review, and continuous learning.

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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关于Expedia Group

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+

员工数

Seattle

总部位置

$6.8B

企业估值

评价

3.8

9条评价

工作生活平衡

4.2

薪酬

3.5

企业文化

4.1

职业发展

4.0

管理层

3.4

75%

推荐给朋友

优点

Supportive work environment and colleagues

Good work-life balance

Great benefits and perks

缺点

Poor management and leadership issues

Compensation below market rate

Organizational chaos from acquisitions

薪资范围

1个数据点

Intern

Intern · Machine Learning Scientist Intern

1份报告

-

年薪总额

基本工资

-

股票

-

奖金

-

面试经验

6次面试

难度

2.8

/ 5

时长

14-28周

面试流程

1

Application Review

2

Recruiter Screen

3

Technical/Coding Assessment

4

Final Interview

5

Offer Decision

常见问题

Coding/Algorithm

Technical Knowledge

Behavioral/STAR

Past Experience

Culture Fit