Amazon.com.ca, ULC

Project/Program/Product Management--Non-Tech, Program Management, selling partner services

SeniorProgramManager,IntellectualPropertyProtection

CA$84–141k Vancouver, British Columbia, Canada FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“Senior Program Manager, Intellectual Property Protection at Amazon.com.ca, ULC. Skills: Program management, Machine learning, Brand protection. Partner with applied scientists. Evaluate machine learning model performance”

What You'll Achieve.

Eliminate false positives; Improve detection accuracy; Ensure high-quality training data; Build to specification; Eliminate thousands of false positives

Industry & Context.

Project/Program/Product Management Non Tech, Program Management, selling partner services
Problems you'll solve

Systematic problem-solving; Root cause analysis; False positive reduction

What They're Looking For.

Must Have

6+ years program management experience, Experience using data and metrics, Experience owning program strategy, Experience communicating results to senior leadership, Experience working cross functionally with tech and non-tech teams

Nice to Have

Master's degree, MBA, Experience with large-scale ML systems, Model performance evaluation experience, Data-driven program strategy experience, Deep understanding of brand protection, Fraud detection knowledge, Abuse prevention knowledge, Trust and safety technologies experience, Project management methodologies experience, Business analysis experience, Process improvement experience

What You'll Do.

Partner with applied scientists

Evaluate machine learning model performance

Make high-judgment decisions

Manage training dataset refresh cycles

Identify text workstream patterns

Conduct root cause analysis

Translate findings into specifications

Present strategic recommendations

Drive alignment across stakeholders

Review detection metrics

Analyze text patterns

Coordinate with engineering

How You'll Work.

Team & Collaboration

Applied scientists; Engineering teams; Directors and VPs; Stakeholders

Communication Scope

Presenting findings; Strategic recommendations

Process & Methodology

Program management, End-to-end delivery

Full Job Description

Are you passionate about leveraging machine learning to protect Amazon's marketplace at scale? We're seeking a Senior Program Manager who will drive our brand protection detection systems through systematic problem-solving and technical expertise. In this role, you'll own the end-to-end program lifecycle for ML-powered detection systems, going 2-3 levels deeper than surface analysis to identify root causes and build solutions that eliminate entire classes of false positives. You'll work directly with applied scientists and engineering teams to translate complex abuse patterns into engineering-ready specifications that scale to hundreds of millions of product listings globally. This position sits at the heart of Amazon's brand protection systems, where your decisions directly determine whether hundreds of millions of product listings are correctly identified as legitimate or infringing. You'll partner with applied scientists on ML model performance, manage golden dataset refresh cycles, optimize image enrollment processes, and conduct root cause analysis on false positive drivers. Your strategic impact will be felt across marketplaces, regions, and languages as you balance precision and recall at unprecedented scale. Key job responsibilities - Partner with applied scientists to evaluate machine learning model performance for brand protection detection systems, making high-judgment decisions that directly impact detection accuracy across billions of listings WW. - Manage high-quality training dataset refresh cycles and text workstream pattern identification across multiple marketplaces and languages to ensure detection models have high-quality training data. - Conduct comprehensive root cause analysis on false positive drivers, going 2-3 levels deeper than surface analysis to identify systematic improvements for detection systems. - Translate findings into detailed engineering-ready specifications with clear, measurable success criteria that enable engineering teams t

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