Senior Manager, Data Science - eBay Live

eBay • San Jose, CA

7d

About The Position

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 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. Join us to build the analytics and AI backbone that powers discovery, engagement, and quality moderation across Live. It's a high‑visibility, priority growth initiative with significant runway - an opportunity to deliver measurable impact at marketplace scale. Opportunity As a Senior Manager of Data Science, you will own the analytics strategy and delivery for an entire domain, defining and landing high‑impact, resource‑intensive programs that align partners to company goals and shape the vision and standards for analytics within eBay Live. You will set technical standards across teams, ensure methodological rigor, and lead cross‑org collaboration with product, engineering, business, and peer analytics to ship scalable solutions and reusable building blocks. This role powers the Data Science engine behind eBay Live's hyper‑growth - sequencing priorities, managing dependencies and risks, and instituting mechanisms that raise quality and velocity across the domain to deliver measurable outcomes.

Requirements

• Hands‑on technical depth: Prototype strategic tools, validate methods, and dive into complex analyses when needed; fluent in SQL/Python, advanced experimentation, econometrics/time‑series, causal inference, dashboarding, and data modeling.
• Domain expert & technical strategist: Deep command of the domain; select appropriate methods; ship production‑grade solutions that scale across teams and use cases.
• Standards and quality bar: Organization‑level authority on analytical rigor - own and enforce coding/analysis/verification standards; review and sign off on complex experiments/econometrics as the point of escalation.
• Cross‑org collaboration: Lead alignment at scale - create mechanisms for shared definitions, transparent prioritization, and pragmatic escalation. Foster a culture where decisions are grounded in experimental evidence and long-term outcomes.
• Influence at scale: Executive‑ready storytelling, whitepapers/strategy docs that shape priorities and funding; trusted advisor who embeds analytics in planning and business reviews.
• Leadership through leaders: Talent magnet and coach; delegate and empower; set mechanisms and processes to track program delivery, partner satisfaction, and quantified business impact.
• AI capabilities & innovation: Foster a culture of innovation; champion high‑impact ML/AI applications and adoption of new analytical tools across the domain.
• Experience: MS/PhD in a quantitative field (e.g., Statistics, Economics, CS) or equivalent experience; typically 9+ years in analytics/data science.
• Extensive track record leading multi‑team analytics programs and owning domain‑level strategy, standards, and delivery; point‑of‑escalation for complex methodological decisions.
• Skills: Advanced experimentation/econometrics/statistical modeling; SQL/Python; dashboarding; architecture‑aware analytics solutioning; stakeholder management across product/engineering/business.
• Communication: Executive‑ready narratives that translate complex analyses into decisions; proven ability to align Director+ audiences and drive cross‑org adoption of analytics standards.

Responsibilities

• Own domain analytics strategy and roadmap; set unified metrics taxonomy and experimentation standards; lead programs that drive sustained improvements in discovery, engagement, and conversion.
• Define the growth analytics agenda across acquisition, onboarding, listing quality, conversion, and retention; govern causal measurement and experimentation; ship reusable measurement assets and instrumentation that scale.
• Lead category-market selection and sequencing; run pilots to de‑risk launches; align partners on metrics taxonomy, definitions, and instrumentation, and track expansion outcomes with clear cadences.
• Own risk modeling and guardrail standards; align business/product/engineering on signals, definitions, and measurement; balance fraud prevention with good‑actor experience through evidence‑based decisions.
• Set event/metric taxonomies, instrumentation quality, and coding/verification standards; build semantic layers/templates; align architecture and data products across teams for consistency and speed.
• Own the domain scorecard and KPI governance; run weekly/monthly/quarterly performance reviews; drive executive‑level decisions with polished, outcome-focused narratives anchored in shared metrics and experiments.

Benefits

• 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).
• Details of participation in these benefit plans will be provided if an employee receives an offer of employment.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Number of Employees: 5,001-10,000 employees