Data Scientist, Row Aop, Analytics Operations and Programs

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

This role focuses on developing and deploying AI/ML products and research models to optimize operations within Amazon's Rest of the World (ROW) region. Responsibilities include analyzing data, developing models using Python/R, creating science-based supply chain solutions, and implementing ML solutions for abuse detection. The role involves working with various teams to deliver high-quality data and science products.

What you'd actually do

  1. Analyze data with statistical and ML techniques.
  2. Develop analysis/model in scripting languages (e.g. Python, R) and statistical/mathematical software (e.g. SAS, Matlab, etc.).
  3. Develop science-based Supply Chain solutions.
  4. Analysis/model documentation.
  5. Develop ML solutions to detect abuse in the network

Skills

Required

  • 1+ 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/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

  • scalable analytics applications, AI/ML products and research models to optimize operation processes
  • Using LLMs to automate analytical processes and insight generation
  • Deep Learning models to synthesize attributes of addresses
  • Abuse detection models to reduce network losses

Other signals

  • Develop scalable analytics applications, AI/ML products and research models to optimize operation processes
  • Using LLMs to automate analytical processes and insight generation
  • Deep Learning models to synthesize attributes of addresses
  • Abuse detection models to reduce network losses