Data Scientist II, Amazon Seller Fee Science (Econometrics and ML), Bengaluru

Job Description

Amazon’s Seller Fee Science team is hiring a Data Scientist II in econometrics and machine learning in Bengaluru to measure and predict Amazon’s profit and loss, with a focus on fee revenue. The team brings together economists, physicists, mathematicians and computer scientists.

At a glance

• Role: Data Scientist II, Seller Fee Science
• Location: Bengaluru, Karnataka, India
• Posted: 25 August 2026
• Experience: 2+ years as a data scientist; 3+ years with SQL/Python/R and ML or statistical modelling; master’s in a STEM field
• Job ID: 10514035
• Apply: open until filled (re-checked 13 October 2026)

About the econometrics and machine learning role

• Turn unclear business questions into well-defined scientific problems
• Improve how fee revenue and other P&L items are measured, predicted and planned
• Build econometric or AI/ML models linking fees, costs and revenue
• Use simulation to validate models and measure business impact
• Work with finance and fee-strategy teams and communicate results clearly

What Amazon is looking for

• 2+ years as a data scientist
• 3+ years with SQL, scripting (such as Python) or statistical software (such as R, SAS or Matlab)
• 3+ years of ML or statistical modelling
• 1+ years guiding researchers and 1+ years working with or evaluating AI systems
• A master’s degree in a STEM field, or equivalent STEM experience

Nice to have

• A PhD in a STEM field
• Experience defining benchmarks for generative AI models
• Experience in cross-disciplinary, multi-team projects

Pay and location

Amazon’s posting does not state a salary; pay is discussed during the hiring process. The role is based in Bengaluru, India.

How to apply

Apply through the official Amazon job posting. Amazon’s posting does not give a closing date, so the role is open until filled; ResearchJobs.in will re-check this listing on 13 October 2026. Amazon lists the minimum and preferred qualifications on the posting; read both before applying. Check the posting for location and work-authorisation details before you apply.

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