Senior Data Scientist - AI-Powered Analytics & Experimentation

eBay

Toronto

On-site

CAD 142,000 - 189,000

Full time

2 days ago
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Benefits offered by this job

RRSP eligibility
Paid time off
Parental leave

Job summary

eBay is seeking a Senior Data Scientist to lead analytics for the Selling Experience team. You will shape product strategy through rigorous experimentation, causal analysis, and scalable data products, partnering with Product and Engineering leaders while mentoring junior data scientists.

Responsibilities include building reusable analytics foundations, developing AI-powered insights, and guiding decision-making with reliable metrics.

Qualifications

  • Master’s or Ph.D. in Data Science, Statistics, Economics, Computer Science, or related quantitative field.
  • 7+ years of experience in product analytics, data science, or similar analytical roles.
  • Deep expertise in experimentation, measurement, causal inference, and statistical modeling.
  • Strong SQL skills and experience with large-scale datasets.
  • Hands-on experience applying LLMs or generative AI to analytics or product use cases.
  • Experience building AI agent systems or self-serve data products; mentoring junior data scientists.

Responsibilities

  • Lead high-impact experimentation and causal analyses across Selling Experience.
  • Partner with Product, Engineering, and business leaders to align measurement approaches and roadmaps.
  • Build scalable analytics foundations, including data models, experimentation frameworks, and tooling.
  • Develop AI-powered analytics agents and self-serve data products to accelerate insights.
  • Mentor junior data scientists and champion data quality and reliability.

Job description

eBay is seeking a Senior Data Scientist to lead analytics for the Selling Experience team. You will shape product strategy through rigorous experimentation, causal analysis, and scalable data products, partnering with Product and Engineering leaders while mentoring junior data scientists.

Responsibilities include building reusable analytics foundations, developing AI-powered insights, and guiding decision-making with reliable metrics.

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