Data Scientist II, Global Supplier Technology Expert

4 weeks ago

Toronto, Ontario, Canada AMEX Full time

About the Role:

We are seeking a highly skilled Data Scientist II to join our Global Supplier Technology team at AMEX. As a key member of our team, you will be responsible for building scalable platforms for the supplier ecosystem, driving business growth, and delivering high-impact changes to customer site and app experiences.

Key Responsibilities:

  • Develop and own the strategic analytic agenda to unlock insights and guide the business.
  • Collaborate with cross-functional partners to ensure alignment between business objectives and data science-driven strategies.
  • Design, execute, and analyze A/B tests using Bayesian or frequentist methodologies to inform high-impact changes.
  • Develop key metrics and reporting to measure initiative performance and enable data-driven decision-making.
  • Apply data science techniques to solve ambiguous problems and build prototypes to drive insights and action.

Requirements:

  • Bachelor's degree in computer science, engineering, math, statistics, economics, or other quantitative discipline; Master's preferred.
  • 3+ years of experience in quantitative analytics, testing, and/or predictive modeling.
  • Proficiency in writing code in structured programming languages (Python, R), GBQ or SQL, and data visualization tools (Data Studio, Looker, Tableau, PowerBI).
  • Experience in leveraging A/B testing and experimentation methodologies for effective product launch measurement.
  • Ability to communicate with and influence senior-level stakeholders on strategic direction.

About AMEX:

AMEX is a leading online retailer for furniture & decor, and we rely on our suppliers to deliver on our core business proposition: delivering great products to our customers quickly and reliably. Our supplier-facing ecosystem enables our 18,000+ supplier-partners to deliver on that promise by providing them with all capabilities they need to successfully manage their e-commerce business.

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