Senior Manager, Data Science – eBay Live

Company: eBay
Apply for the Senior Manager, Data Science – eBay Live
Location: Greater London
Job Description:

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 The Role And Team

eBay Live is eBay’s interactive live shopping platform where sellers and creators broadcast in real time and buyers interact through chat, bidding, and instant purchases. It combines entertainment, community, and commerce into an engaging, trust‑supported way to explore and shop. Join us to develop the analytics and AI foundation that drives discovery, engagement, and quality moderation throughout Live. It’s a high‑profile, priority growth project with substantial potential—an opportunity to achieve measurable impact at marketplace scale.

What You Will Accomplish

  • Buyer Product Analytics: Lead the domain analytics strategy and roadmap; define a consistent metrics taxonomy and experimentation protocols; guide programs that promote ongoing progress in user acquisition, interaction, and conversion.
  • Seller Product & Seller Success: 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 and market selection and sequencing. Run pilots to reduce launch risks. Align partners on metrics taxonomy, definitions, and instrumentation. Track expansion outcomes regularly.
  • Trust & Safety: Own risk modelling and guardrail standards; align business/ product/engineering on signals, definitions, and measurement; balance fraud prevention with good‑actor experience through evidence‑based decisions.
  • Data Foundation & Instrumentation: 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.
  • Business Performance: Lead the domain scorecard and governance of important metrics. Run weekly, monthly, and quarterly performance reviews. Drive executive‑level decisions with clear, outcome‑focused narratives based on shared metrics and experiments.

What You Will Bring

  • Demonstrates hands‑on technical depth by prototyping strategic tools and validating methods. Performs sophisticated analyses as needed. Proficient in SQL/Python, advanced experimentation, econometrics/time‑series, causal inference, dashboarding, and data modelling.
  • Domain expert & technical strategist: Deep command of the domain; select appropriate methods; ship production‑grade solutions that scale across teams and use cases.
  • As the organisation‑level authority on analytical rigour, you own coding, analysis, and verification standards. You review and sign off on complex experiments and econometrics as the point of escalation.
  • Cross‑org collaboration: Guide alignment on a broad scale – develop processes for common definitions, clear prioritisation, and practical resolution of obstructive problems. Encourage a culture where choices are based on experimental data and long‑term results.
  • Influence at scale: Executive‑ready storytelling, whitepapers/strategy docs that build priorities and funding; trusted advisor who embeds analytics in planning and business reviews.
  • Leadership through leaders: Talent magnet and mentor; delegate and empower; set mechanisms and processes to track program delivery, partner happiness, and quantified business impact.
  • AI capabilities & innovation: Encourage a culture of innovation; promote high‑impact ML/AI applications and the integration of new analytical tools throughout the field.
  • Experience: Advanced degree or equivalent experience in a quantitative field (for example, Statistics, Economics, Computer Science). Senior‑level track record leading multi‑team analytics programs; owning domain‑level strategy, standards, and delivery; and handling the highest‑level resolution for complex methodological decisions. Seniority is assessed by demonstrated scope and outcomes rather than fixed years of experience.
  • Skills: Advanced experimentation, econometrics, and statistical modelling. Proficiency in SQL and Python with production‑scale datasets. Experience in dashboarding and data storytelling. Developing analytics solutions with data and ML platform teams. Managing partnerships across product, engineering, and business.
  • Communication: Executive‑ready narratives that translate complex analyses into clear decisions; proven ability to align Director+ audiences and drive cross‑org adoption of analytics standards.

eBay 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.

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Posted: April 17th, 2026