Data Science I, Scot Forecasting & Lab

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

This role focuses on improving existing machine learning methodologies within Amazon's supply chain optimization team. The Data Scientist will analyze large datasets, develop and test model enhancements, fine-tune parameters, and formalize assumptions about model behavior. They will also contribute to the research community by publishing papers and collaborating with other scientists and academic researchers. The role requires strong analytical and communication skills to interface with business customers and stakeholders.

What you'd actually do

  1. Analysis of large amounts of data from different parts of the supply chain and their associated business functions
  2. Improving upon existing machine learning methodologies by developing new data sources, developing and testing model enhancements, running computational experiments, and fine-tuning model parameters for new models
  3. Formalizing assumptions about how models are expected to behave, creating definitions of outliers, developing methods to systematically identify these outliers, and explaining why they are reasonable or identifying fixes for them
  4. Communicating verbally and in writing to business customers with various levels of technical knowledge, educating them about our research, as well as sharing insights and recommendations
  5. Utilizing code (Python, R, Scala, etc.) for analyzing data and building statistical and machine learning models and algorithms

Skills

Required

  • Python
  • R
  • Scala
  • SQL
  • statistical modeling
  • machine learning

Nice to have

  • Hadoop
  • Spark
  • Map-reduce
  • Hive
  • SPSS
  • SAS
  • S-PLUS

What the JD emphasized

  • strong analytical and communication skills
  • sophisticated algorithms
  • learning from large amounts of data
  • improving upon existing machine learning methodologies
  • developing new data sources
  • developing and testing model enhancements
  • running computational experiments
  • fine-tuning model parameters
  • formalizing assumptions
  • creating definitions of outliers
  • developing methods to systematically identify these outliers
  • explaining why they are reasonable or identifying fixes for them
  • communicating verbally and in writing to business customers
  • innovative research tools
  • implementation of sophisticated models on big data
  • analytical problem solver
  • investigations and algorithms
  • synthesizing and communicating insights and recommendations

Other signals

  • optimizing complex trade-offs
  • sophisticated algorithms
  • learning from large amounts of data
  • improving upon existing machine learning methodologies
  • developing new data sources
  • developing and testing model enhancements
  • running computational experiments
  • fine-tuning model parameters
  • creating definitions of outliers
  • developing methods to systematically identify these outliers
  • explaining why they are reasonable or identifying fixes for them
  • innovative research tools
  • implementation of sophisticated models on big data
  • analytical problem solver
  • investigations and algorithms
  • synthesizing and communicating insights and recommendations