Skills this job asks for
LeadershipData engineeringA/B testingProduct managementMachine learningStatistics
Add your CV (free) to see which of these your CV is missing.
Sponsorship verdict
Sponsorship possible
One solid signal, not two. Worth applying, and worth asking about sponsorship early.
-
✓
Employer is on a government sponsor recordThe US Department of Labor certified 478 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first.
-
?
The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
-
?
No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area.
-
✓
What Ebay INC paid sponsored hires in similar roles15 certified filings for “Manager, Data Science - Analytics 2” (Information Technology Project Managers) in CA: $198k–$220k, median $206k.
-
✓
Confirmed live todayWhen a source last listed this job as open.
Details and sources
- Employer is on a government sponsor record
- The US Department of Labor certified 478 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. Source: LCA disclosure data (US Department of Labor (OFLC)).
- No salary bar for this route
- H-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
- What Ebay INC paid sponsored hires in similar roles
- 15 certified filings for “Manager, Data Science - Analytics 2” (Information Technology Project Managers) in CA: $198k–$220k, median $206k. Most were filed at wage level III (53%) — 3 lottery entries, ≈46% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).
US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).
A verdict summarises public evidence. It is not legal advice and never a guarantee: the employer and the immigration authority decide. Sign in to factor in where you can already work.
About the role
At eBay, 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.
About eBay Live
eBay Live is eBay’s interactive live shopping platform where sellers and creators broadcast in real time and buyers participate through chat, bidding, and instant purchases. It combines entertainment, community, and commerce into an engaging, trust‑based approach to discover and shop. Join us to develop the analytics and AI foundation that drives discovery, engagement, and quality moderation throughout Live. It’s a highly visible, priority growth project with substantial potential—a chance to create measurable impact at marketplace scale.
Opportunity
In your role as a Staff Data Scientist, you will combine advanced analysis skills with initial leadership responsibilities. You will manage complete analytical projects, prioritize unclear problems, choose suitable methods, maintain quality, and share insights that drive decisions. Additionally, you will define protocols for analysis, evaluate outputs from the team, and develop solutions (including data pipelines and tracking schemas) alongside engineering to expand product-impact analytics for eBay Live.
Specifically, you will contribute to developing the Data Science engine that drives eBay Live’s rapid growth across Seller Product & Seller Success, Buyer Product, Categories/Markets expansion, Trust & Safety, Data Foundation, and Business Performance—providing measurable results through causal measurement, experimentation, marketplace and risk modeling, and production‑quality insights/dashboards.
What You’ll Do
You will focus on one of the following pillars, while mentoring and improving analysis quality:
• Own end-to-end analyses for live commerce features. Define product metrics and tracking. Lead experiments that inform the roadmap and growth. Review peers’ work to uphold rigor.
• Seller Product & Seller Success: Build and govern growth experiments; analyze onboarding, listing quality, conversion, and retention; propose interventions and measurement plans; enforce review standards and reproducibility.
• Model category–market dynamics and size opportunities. Build selection and expansion frameworks. Advise sequencing and launch decisions. Architect lightweight data assets, such as derived tables, to unblock analyses.
• Analyze marketplace risk signals and collaborate on guardrail building and monitoring. Apply practical ML/AI techniques. Refine test builds and metrics to reduce false positives while protecting good actors.
• Data Foundation & Instrumentation: Clarify metric/event taxonomies; ensure instrumentation quality; build curated datasets and dashboards; troubleshoot data issues; automate recurring tasks with a product‑first approach.
• Business Performance: Own important metrics within scope; synthesize daily/weekly/monthly/quarterly performance narratives; surface opportunities/risks; influence decisions with evidence‑based recommendations.
What You Bring
• Technical leadership and depth: Lead analyses end‑to‑end, from prioritization to presentation; select robust methods (advanced experimentation, econometrics, statistical modeling) for complex measurem
Apply on employer site ↗