• Join us to build the analytics and AI backbone that powers discovery, engagement, and quality moderation across Live

As a Staff Data Scientist, you will be both a highly skilled analyst and a beginning team leader - owning end‑to‑end analytical projects, scoping ambiguous problems, selecting the right methods, ensuring quality, and presenting insights to drive action

• You will also set standards for analytical best practices, review team outputs, and architect solutions (e.g., data pipelines, tracking schemas) in partnership with engineering to scale product‑impacting analytics for eBay Live

Specifically you will be part of the journey to build the Data Science engine that powers eBay Live hyper‑growth across Seller Product & Seller Success, Buyer Product, Categories/Markets expansion, Trust & Safety, Data Foundation, and Business Performance - delivering measurable outcomes through causal measurement, experimentation, marketplace and risk modeling, and production‑grade insights/dashboards

• You will focus on one of the following pillars, while coaching and raising the bar for analysis quality:
• Buyer Product Analytics: Own end‑to‑end analyses for live commerce features; define product metrics and tracking; lead experiments that inform roadmap and growth; review peers’ work to uphold rigor
• Seller Product & Seller Success: Design and govern growth experiments; analyze onboarding, listing quality, conversion, and retention; propose interventions and measurement plans; enforce review standards and reproducibility
• Categories & Markets Expansion: Model category–market dynamics; size opportunities; build selection/expansion frameworks; advise sequencing and launch decisions; architect lightweight data assets (e.g., derived tables) to unblock analyses
• Trust & Safety: Analyze marketplace risk signals; partner on guardrail design and monitoring; apply practical ML/AI; refine test designs 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 mindset
• Business Performance: Own KPIs within scope; synthesize daily/weekly/monthly/quarterly performance narratives; surface opportunities/risks; influence decisions with evidence‑based recommendations
• Technical leadership and depth: Lead analyses end‑to‑end, from scoping to presentation; select robust methods (advanced experimentation, econometrics, statistical modeling) for complex measurements
• Review standards and quality bar: Establish and enforce coding, analysis, and verification best practices; conduct code/analysis reviews; ensure stakeholder‑ready outputs
• Architecting solutions: Identify and drive data solution needs (new pipelines, tracking schemas, derived tables) with engineering; design for scale and maintainability
• Ownership of domain and stakeholder management: Operate autonomously as the primary analytics partner for your area; prioritize high‑impact work; manage cross‑functional project delivery to outcomes

Player‑coach leadership: Balance hands‑on contributions with mentoring and guidance; set hiring/engagement standards; build a culture of continuous learning and positivity

• Applied AI/ML integration: Spot high‑impact opportunities for ML/AI and automation; prototype solutions and partner with specialists to productionize where appropriate
• Influential communication: Distill complex analyses into crisp narratives; present insights and recommendations to senior stakeholders (directors/VPs) to drive decisions
• Education/experience: MS in a quantitative field (e.g., Statistics, Economics, CS) or equivalent experience; typically 7+ years in analytics/data science with multiple production‑quality projects or complex analytical programs
• Skills: Strong SQL/Python; experimentation design; statistical/econometric modeling; dashboarding; familiarity with marketplace dynamics and product analytics

Communication: Executive‑ready storytelling that translates analysis into actionable recommendations and influences product decisions

$170,400 - $227,500

• Base pay offered may vary depending on multiple individualized factors, including location, skills, and experience

The total compensation package for this position may also include other elements, including a target bonus and restricted stock units (as applicable) in addition to a full range of medical, financial, and/or other benefits (including 401(k) eligibility and various paid time off benefits, such as PTO and parental leave) If hired, employees will be in an “at-will position” and the Company reserves the right to modify base salary (as well as any other discretionary payment or compensation program) at any time, including for reasons related to individual performance, Company or individual department/team performance, and market factors