eBay-posted 9 days ago
Full-time • Mid Level
San Francisco, CA
5,001-10,000 employees

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 team and the role: The Search Ranking and Monetization Team is the biggest contributor to eBay’s advertising program. We innovate at the heart of e-commerce search and advertising, with the ambitious goal of redefining e-commerce advertising. We craft optimized experiences for buyers and sellers on eBay. We innovate rapidly in this space and there is no shortage of new challenges for motivated individuals. We are looking for stellar applied researchers to join us and build the next generation of online advertising products in eBay search. If you enjoy the scale and technical complexity of advertising and want to be at the frontier of applied research in advertising in e-commerce, join now. Help us redefine advertising at eBay.

  • Seek scientifically valid solutions that deliver real value to eBay customers
  • Build machine learning models and data pipelines to deliver insightful yet practical solutions
  • Work with multiple teams to help promote standard scientific methodologies and processes in your field
  • Present key technical and novel research work in public forums and conferences
  • MS or PhD in Computer Science, Statistics, Mathematics, or equivalent
  • 0-1 years (with PhD) or 1-3 years (with MS) of industrial experience in a related field
  • Industrial experience with one or more of the following: classification, regression, recommendation systems, targeting systems, ranking systems, fraud detection, online advertising, or related
  • Experience in big data processing, e.g. Hadoop, SQL, Spark
  • Experience with Python or R, and Java or Scala or C/C++
  • 2 or more related publications in quality conferences or journals
  • 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.
© 2024 Teal Labs, Inc
Privacy PolicyTerms of Service