Manager – Pick-up and Drop-off Pricing & Monetization

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.

eBay is a global marketplace connecting millions of buyers and sellers across more than 190 markets. People come to eBay to discover unique and pre-loved goods, pursue their interests, and grow businesses. Our purpose is to connect people and build communities to create economic opportunity for all.

About the team and the role

PUDO (pick-up and drop-off) is a major central initiative to create a materially lower-cost shipping proposition for eBay and Depop. A central question is whether lower shipping prices and other customer interventions actually change buyer and seller behavior enough to create incremental marketplace value.

This role owns the analytical evidence behind those decisions. This person will design and evaluate pricing and incentive experiments, measure elasticity and incrementality, understand how response varies across customer and inventory segments, and determine whether observed behavior supports the assumptions in the PUDO economic model.

What you will accomplish

• Design and evaluate pricing, subsidy, incentive and offer experiments that test how buyers and sellers respond to changes in the PUDO proposition
• Measure shipping-price elasticity, adoption, repeat behavior and incrementality across customer, seller, category, ASP, geography and parcel-flow segments
• Distinguish true marketplace growth from shipment substitution, promotional lift, mix shift and other effects that can make adoption appear stronger than it is
• Build cohort and causal analyses that determine whether lower shipping prices create incremental conversion, transaction frequency, GMV or addressable low-ASP demand
• Partner with the Economics leader to translate observed customer response into pricing, subsidy, break-even and scale recommendations
• Establish measurement plans before tests launch, including hypotheses, success metrics, control / comparison groups, guardrails and decision thresholds
• Diagnose performance when results differ from expectation: identify the likely causal drivers, test competing explanations and recommend the next experiment or business action
• Build reusable analytical tools and automated reporting that allow the team to evaluate pricing and adoption decisions quickly without creating a large analytics support layer

What you will bring

• Strong SQL skills and demonstrated ability to independently query, structure and analyze large marketplace or customer datasets
• Strong statistical and experimental reasoning, including experience with A/B testing, cohort analysis, elasticity measurement, causal inference or comparable quantitative methods
• Ability to distinguish correlation from causation and recognize common analytical traps such as selection bias, mix shift, immature cohorts, seasonality and simultaneous interventions
• Strong commercial judgment: able to move from analysis to a clear answer about what the business should do differently
• Experience analyzing customer behavior, pricing, marketplace dynamics or monetization. Experience in marketplaces, consumer technology, logistics or network businesses is particularly relevant.
• Ability to communicate complex analytical findings clearly to senior non-technical audiences without hiding uncertainty or overstating the evidence
• Strong proficiency with AI and modern analytical tools, with a bias toward automating recurring analysis and accelerating the test-learn cycle
• Bachelor’s degree or equivalent practical experience in economics, statistics, data science, finance, engineering, business or a related quantitative field

How we will measure success

Success means the business can make pricing and investment decisions with increasing confidence because we understand what actually changes customer behavior.

The role succeeds when we can quickly distinguish:

• price sensitivity from noise;
• incremental transactions from shipment substitution;
• trial from durable repeat behavior;
• promotional response from sustainable adoption; and
• modeled assumptions from behavior we have actually proven.

Additional Details

The base pay range for this position is expected in the range below:

C$102,800 - C$137,200

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 RRSP eligibility, 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.

This job posting relates to an existing vacancy within eBay.

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, and disability, or other legally protected status. If you have a need that requires accommodation, please contact us at [email protected]. We will make every effort to respond to your request for accommodation as soon as possible. View our accessibility statement to learn more about eBay's commitment to ensuring digital accessibility.

We use cookies to enhance your experience and may use AI tools for administrative tasks in the hiring process. To learn how we handle your personal data and use AI responsibly, please visit our Talent Privacy Notice, Privacy Center and AI Hiring Guidelines.