Data Scientist, Ies Cfx & Prime

Amazon Amazon · Big Tech · IN, KA, Bengaluru · Data Science

This role focuses on developing and deploying machine learning systems to detect fraudulent customer behavior, analyze customer risk, and optimize customer promotions within Amazon's online marketplace. It involves building end-to-end ML solutions in a production environment, collaborating with cross-functional teams, and applying advanced statistical techniques and GenAI technology.

What you'd actually do

  1. Use machine learning and statistical techniques to create scalable abuse detection solutions that identify fraudulent customer behavior, rings of accounts, identity change, holistic customer risk and marketplace manipulation schemes
  2. Innovate with the latest GenAI technology to build highly automated solutions for efficient customer promotions
  3. Design, develop and deploy end-to-end machine learning solutions in the Amazon production environment to delight Amazon customers
  4. Collaborate with cross-functional teams to develop comprehensive ML/statistical models that can scale to millions of customers and 10+ countries

Skills

Required

  • 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
  • 3+ years of data/research scientist, statistician or quantitative analyst in an internet-based company with complex and big data sources experience
  • Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)

Nice to have

  • Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)
  • Knowledge of statistical packages and business intelligence tools such as SPSS, SAS, S-PLUS, or R
  • Knowledge of machine learning concepts and their application to reasoning and problem-solving
  • Experience with clustered data processing (e.g., Hadoop, Spark, Map-reduce, and Hive)
  • Experience working with or evaluating AI systems
  • Experience applying quantitative analysis to solve business problems and making data-driven business decisions
  • Experience effectively communicating complex concepts through written and verbal communication

What the JD emphasized

  • end-to-end machine learning solutions
  • scale to millions of customers

Other signals

  • Develop and deploy machine learning systems
  • Analyze millions of customer interactions daily
  • Build highly automated solutions for efficient customer promotions
  • Design, develop and deploy end-to-end machine learning solutions in the Amazon production environment