Data Scientist II, Selection Growth Science
Pubblicato il 02-10-2026 - Amazon in Asti
Data Scientist II, Selection Growth Science
Join us in the evolution of Amazon's Seller business The Selling Partner Selection Succ organization is the growth and development engine for our Store. Partnering with business, product, and engineering, we catalyze SP growth with comprehensive and accurate data, unique insights, and actionable recommendations and collaborate with WW SP facing teams to drive adoption and create feedback loops. We strongly believe that any motivated SP should be able to grow their businesses and reach their full potential supported by Amazon tools and resources.
Key job responsibilities
- Identify opportunities to improve SP growth and translate those opportunities into science problems via principled GenAI solutions.
- Design and execute roadmaps for complex science projects to help SP have a delightful selling experience while creating long term value for our shoppers.
- Work with our engineering partners and draw upon your experience to meet latency and other system constraints.
- Be responsible for communicating our science innovations to the broader internal & external scientific community.
Basic Qualifications
- 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- 2+ years of data scientist experience
- 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
- Experience applying theoretical models in an applied environment
Preferred Qualifications
- PhD in computer science, mathematics, statistics, machine learning or equivalent quantitative field
- Experience in a ML or data scientist role with a large technology company
- Demonstrated experience leveraging generative AI tools to enhance workflow efficiency and productivity, with the ability to craft effective prompts and critically evaluate AI-generated outputs in a professional setting