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채용eBay

Data Scientist, Selling Experience

eBay

Data Scientist, Selling Experience

eBay

Bengaluru, India

·

On-site

·

Full-time

·

2w ago

At e Bay, we're more than a global ecommerce leader — we’re changing the way the world shops and sells. Our platform empowers millions of buyers and sellers in more than 190 markets around the world. We’re committed to pushing boundaries and leaving our mark as we reinvent the future of ecommerce for enthusiasts.

Our customers are our compass, authenticity thrives, bold ideas are welcome, and everyone can bring their unique selves to work — every day. We're in this together, sustaining the future of our customers, our company, and our planet.

Join a team of passionate thinkers, innovators, and dreamers — and help us connect people and build communities to create economic opportunity for all.

We are seeking a Data Scientist to help build the future of AI-powered selling experiences. In this role, you will partner closely with Product and Engineering teams to develop analytics, experimentation strategies, and data-driven insights that simplify listing flow, improve listing quality, and accelerate seller growth.

You will work on high-impact initiatives such as AI-assisted listing flows, personalized seller guidance, LLM-powered insights, and scalable experimentation frameworks that directly influence product roadmap and business outcomes. This role is ideal for a strong senior data scientist who can independently own analytics workstreams, apply structured thinking to ambiguous problems, and translate data into actionable recommendations that improve both user experience and business performance.

Key Responsibilities

  • Design, implement, and analyze A/B tests to evaluate product features and AI-powered experiences

  • Define success metrics, measurement frameworks, and experimentation strategies to support product development and launches

  • Analyze user behavior, product funnels, and engagement patterns to find opportunities to improve seller activation, efficiency, and success

  • Partner closely with Product and Engineering teams to inform roadmap prioritization, feature design, and iteration decisions

  • Conduct deep-dive analyses to understand performance across seller segments, categories, and product workflows

  • Build scalable data pipelines, dashboards, and monitoring tools to track product performance and experimentation results

  • Find opportunities to use AI and advanced analytics to improve seller experience and product effectiveness

  • Translate complex analyses into clear, actionable insights and recommendations for technical and non-technical partners

  • Improve analytics workflows and tooling to increase insights velocity, scalability, and impact

  • Ensure data quality, tracking integrity, and measurement reliability to support accurate experimentation and decision-making

Required Qualifications

  • Master’s degree or equivalent in Data Science, Statistics, Economics, Computer Science, or a related quantitative field

  • Master's + 4-7 years or 6-9 years of professional experience in product analytics, data science, or a related analytical role

  • Strong SQL skills and experience working with large-scale, complex datasets

  • Hands-on experience designing, executing, and analyzing A/B tests

  • Solid foundation in statistics, experimentation, modeling and causal inference

  • Strong analytical thinking, problem-solving, and structured reasoning skills

  • Experience partnering cross-functionally with Product and Engineering teams

  • Ability to independently own analyses and translate data into actionable product insights

  • Strong communication skills with the ability to influence both technical and non-technical stakeholders

Preferred Qualifications

  • Experience working on marketplace, e-commerce platforms or large-scale technology products

  • Experience with AI-powered product features or LLM/GenAI

  • Experience building scalable analytics tools, data models, or experimentation frameworks

Why Join This Team

You will play a key role in shaping the future of AI-powered selling at e Bay. Your work will directly influence product strategy, accelerate innovation, and improve the experience for millions of sellers worldwide. You will operate at the intersection of analytics, product, and AI—solving high-impact problems and helping drive marketplace growth through data-driven decision-making.

Additional Details

e Bay is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, sexual orientation, gender identity, veteran status, and disability, or other legally protected status. If you have a need that requires accommodation, please contact us at talent@ebay.com. We will make every effort to respond to your request for accommodation as soon as possible. View our accessibility statement to learn more about e Bay's commitment to ensuring digital accessibility for people with disabilities.

We use cookies to enhance your experience and may use AI tools for administrative tasks in the hiring process. To learn how we handle your personal data and use AI responsibly, please visit our Talent Privacy Notice, Privacy Center, and AI Hiring Guidelines.

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eBay 소개

eBay

eBay

Public

eBay Inc. is an American multinational e-commerce company based in San Jose, California, that allows users to buy or view items via retail sales through online marketplaces and websites in 190 markets worldwide.

10,001+

직원 수

San Jose

본사 위치

$28.1B

기업 가치

리뷰

3.8

5개 리뷰

워라밸

4.2

보상

2.5

문화

4.0

커리어

2.8

경영진

3.5

장점

Good work-life balance

Great culture and environment

Nice colleagues and supportive people

단점

Limited opportunities for growth

Old technology and systems

Call quotas and difficult customers

연봉 정보

2,731개 데이터

Junior/L3

Mid/L4

Senior/L5

Junior/L3 · Data Science Analyst 2

1개 리포트

$174,200

총 연봉

기본급

$134,000

주식

-

보너스

-

$174,200

$174,200

면접 경험

4개 면접

난이도

3.0

/ 5

소요 기간

14-28주

경험

긍정 0%

보통 75%

부정 25%

면접 과정

1

Application Review

2

Recruiter Screen

3

Online Assessment

4

Technical Interview

5

Team Matching

6

Offer

자주 나오는 질문

Coding/Algorithm

Technical Knowledge

Behavioral/STAR

Past Experience