Jobs
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.
Senior Manager – Data Science
e Bay Live – Categories & Markets
About e Bay Live:
e Bay Live is e Bay’s interactive live shopping experience where sellers and creators stream in real time and buyers engage through chat, bidding, and instant purchases. It blends entertainment, community, and commerce into a dynamic, trust-backed way to discover and shop.
As Live scales globally, thoughtful category expansion, programming strategy, and market development are critical to building a differentiated and sustainable ecosystem. Join us to shape how Live grows across verticals and geographies — grounded in rigorous measurement, strategic insight, and marketplace economics.
Opportunity
As Senior Manager – Data Science for Categories & Markets, you will lead the analytical strategy that informs which categories to scale, how to program Live events, how to prioritize markets, and how to optimize supply-demand dynamics.
This is not a traditional feature-level product analytics role. Instead, you will operate at the marketplace and portfolio level — evaluating programming strategies, category investments, and expansion plays using causal inference, quasi-experimental methods, and observational studies.
You will serve as the senior analytics thought partner to Category Leads and Market GMs, influencing multi-quarter strategy and capital allocation decisions.
What You’ll Do
Category Strategy & Portfolio Analytics
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Evaluate category performance across GMV, engagement, liquidity, and seller health.
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Identify whitespace opportunities and sequencing for vertical expansion.
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Build frameworks to assess category maturity and ecosystem sustainability.
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Model supply–demand balance and marketplace efficiency across verticals.
Programming Impact & Causal Measurement
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Design experiments to measure impact of Live programming initiatives (featured events, creator partnerships, curated drops).
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Apply causal inference methods (diff-in-diff, synthetic controls, matching, uplift modeling) to isolate incremental impact.
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Develop guardrails to distinguish short-term GMV spikes from sustainable growth.
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Quantify halo and cross-category spillover effects.
Observational & Quasi-Experimental Studies
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Conduct deep observational studies to understand behavioral shifts across cohorts and markets.
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Leverage natural experiments and policy changes to assess impact when randomization is not feasible.
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Develop robust counterfactual frameworks for non-randomized programming decisions.
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Evaluate long-term retention and ecosystem health effects of category-level interventions.
Market Expansion & International Scaling
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Size opportunities across new markets using marketplace dynamics and local category behavior.
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Evaluate launch readiness using supply depth, demand density, and creator ecosystem strength.
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Develop prioritization frameworks for resource allocation across markets.
Strategic Narrative & Executive Influence
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Translate complex modeling outputs into clear recommendations for senior leadership.
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Synthesize monthly/quarterly category health narratives.
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Influence investment decisions with structured, evidence-backed tradeoff analysis.
What You Bring
Advanced Causal & Observational Analytics
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Deep experience in causal inference (diff-in-diff, matching, synthetic control, CUPED, uplift modeling).
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Strong understanding of bias, confounding, and identification strategy in non-randomized environments.
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Experience evaluating large-scale programming or marketplace interventions.
Marketplace & Ecosystem Thinking
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Strong intuition for supply–demand dynamics and liquidity in two-sided platforms.
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Ability to distinguish growth driven by structural ecosystem improvements vs. short-term promotional lift.
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Comfort operating at category, portfolio, and market levels.
Technical Strength
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Advanced SQL and Python proficiency.
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Experience building robust analytical datasets across multiple sources.
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Familiarity with ML where appropriate (e.g., demand forecasting, cohort modeling), though not primarily a pure ML role.
Strategic Leadership
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Ability to independently define analytical roadmaps aligned to business priorities.
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Strong prioritization judgment in ambiguous environments.
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Experience managing and mentoring data scientists.
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Comfortable presenting to Director/VP-level stakeholders.
Storytelling & Influence
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Ability to communicate trade-offs clearly (growth vs. efficiency, short-term vs. durable impact).
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Structured, hypothesis-driven problem solving.
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Executive-ready communication skills.
Why This Role is Unique
This role sits at the intersection of:
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Strategy
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Marketplace economics
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Programming effectiveness
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International expansion
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Advanced causal analytics
You will directly shape how e Bay Live scales across categories and markets, ensuring growth is both measurable and durable.
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.
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About eBay

eBay
PublicBuy, sell, and discover.
10,001+
Employees
San Jose
Headquarters
Reviews
3.8
5 reviews
Work Life Balance
4.2
Compensation
2.5
Culture
4.0
Career
2.8
Management
3.5
Pros
Good work-life balance
Great culture and environment
Nice colleagues and supportive people
Cons
Limited opportunities for growth
Old technology and systems
Call quotas and difficult customers
Salary Ranges
2,741 data points
Mid/L4
Mid/L4 · Business Process Analyst 2
3 reports
$111,775
total / year
Base
$97,196
Stock
-
Bonus
-
$111,775
$111,775
Interview Experience
4 interviews
Difficulty
3.0
/ 5
Duration
14-28 weeks
Experience
Positive 0%
Neutral 75%
Negative 25%
Interview Process
1
Application Review
2
Online Assessment (CodeSignal)
3
Technical Phone Screen
4
Technical Interview Rounds
5
Final Review
Common Questions
Coding/Algorithm
Technical Knowledge
Problem Solving
Data Structures
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