Data Scientist, Aws Support Capacity Planning

Amazon Amazon · Big Tech · Seattle, WA · Data Science

Data Scientist role at AWS focused on capacity planning, using statistical modeling, machine learning, and optimization to forecast contact volumes and drive operational improvements. The role involves building and managing modeling projects and forecasting solutions, requiring expertise in data science, forecasting, optimization, and machine learning.

What you'd actually do

  1. model contact and volume forecasting
  2. discover insights and identify opportunities through the use of statistics, machine learning, and combinatorial optimization problems to drive business and operational improvements
  3. partner with data engineering, tooling team, operations, training, workforce management and finance teams, driving optimization and prediction solutions across the network influencing the long-term strategy of the business
  4. build and manage modeling projects, forecasting solutions, identify data requirements, build methodology and tools that are statistically grounded
  5. work in Python or R, building forecasting, predictive and optimization models

Skills

Required

  • 2+ years of data scientist experience
  • 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 machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
  • Experience applying theoretical models in an applied environment

Nice to have

  • Experience in Python, Perl, or another scripting language
  • Experience in a ML or data scientist role with a large technology company

What the JD emphasized

  • The ability to embrace this ambiguity and work with a highly distributed team of experts is critical.

Other signals

  • modeling contact and volume forecasting
  • discovering insights and identifying opportunities through the use of statistics, machine learning, and combinatorial optimization problems
  • build and manage modeling projects, forecasting solutions
  • statistically grounded methodology and tools