Data Scientist Ii, Nasc S&op

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

The Data Scientist II will design and implement solutions to address complex business questions using advanced statistical and machine learning (ML) techniques, experimentation, and big data. In this role, you will build scalable ML models, apply advanced analysis technique and statistical concepts to draw insights from massive datasets, and create intuitive science models and data visualizations. You can contribute to each layers of a data solution – you will work closely with business intelligence engineers and product managers to obtain relevant datasets and prototype predictive analytic models, and implement data pipeline to productionize your models, and review key results with business leaders and stakeholders. Your work exhibits a balance between scientific validity and business practicality.

What you'd actually do

  1. Development of scalable data science solutions catering to volume and cube forecasting for NASC Sales and Operation Planning Team.
  2. Working closely with Network Planners, Product Managers, Data Scientists, Business Intelligence Engineers, and various planning teams to drive business decisions and alignment with business stakeholders.
  3. Development of scalable data science solutions to audit and optimize our NASC network.
  4. Development and execution of analytical tools to model our transportation network.
  5. Contribute to the strategy for network design, prioritize technical and operational initiatives, evaluate and set stakeholders expectations.

Skills

Required

  • 3+ 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

  • turn ambiguous business questions into clearly defined problems
  • develop quantifiable metrics and robust machine learning models from imperfect data sources
  • deliver results that meet high standards of data quality, security, and privacy

Other signals

  • build scalable ML models
  • apply advanced analysis technique and statistical concepts
  • create intuitive science models and data visualizations
  • prototype predictive analytic models
  • implement data pipeline to productionize your models