Applied Researcher 1

eBay•Toronto, ON

About The Position

The Search Ranking and Monetization team sits at the core of eBay’s marketplace, powering the search and advertising experiences that connect millions of buyers and sellers every day. As the largest contributor to eBay’s advertising program, the team focuses on redefining e-commerce advertising through cutting-edge machine learning, large-scale experimentation, and a strong focus on customer value. We are looking for applied researchers who are excited by the scale and complexity of online advertising and search. In this role, you will design and deploy advanced models that shape how listings are ranked, how ads are served, and how buyers discover the inventory they love. You will work closely with partner teams across product, engineering, and analytics, and you will have opportunities to share your work internally and in external forums and conferences.

Requirements

MS or PhD in Computer Science, Statistics, Mathematics, or a related quantitative field, or equivalent practical experience.
1–3 years of relevant industry experience with a PhD, or 3–5 years with an MS, working in areas such as online advertising, ranking, recommendation, targeting, fraud detection, or related fields.
Hands-on experience applying machine learning techniques (e.g., classification, regression, ranking, recommendation) in large-scale, real-world systems.
Proficiency with big data tools and technologies such as Hadoop, SQL, and Spark, and comfort working with large, complex datasets.
Strong programming skills in Python or R, and in at least one of Java, Scala, or C/C++, with a focus on building production-quality solutions.
A track record of scientific impact demonstrated by 2 or more related publications in reputable conferences or journals, and the ability to clearly communicate research findings to both technical and non-technical audiences.

Responsibilities

Deliver scientifically robust solutions that improve key buyer and seller outcomes, such as relevance, engagement, and marketplace efficiency.
Design, build, and iterate on machine learning models and data pipelines that power ranking, recommendation, and advertising products in eBay search.
Partner with cross-functional teams to define problem statements, validate hypotheses, and translate research into scalable, production-ready solutions.
Promote and standardize scientific methodologies, experimentation practices, and best-in-class evaluation frameworks across the organization.
Share technical and research contributions through internal forums and external conferences, helping position eBay as a leader in e-commerce advertising.
Continuously expand your expertise in large-scale machine learning, big data technologies, and online experimentation while mentoring and learning from peers.