ML Scientist for Transportation Optimization

Amazon

Bellevue (WA)

On-site

USD 143,000 - 193,000

Full time

11 days ago

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Benefits offered by this job

Health insurance
401(k) matching
Paid time off
Parental leave

Job summary

Amazon's Middle Mile Surface Research Science seeks an Applied Scientist to invent and build machine learning models that improve how Amazon plans and operates its transportation network.

You will design and deploy forecasting and prediction models, tackle trailer imbalance forecasting, and work with product, engineering, and operations partners to deliver results that impact billions in decisions and enhance the delivery experience for customers.

Qualifications

  • PhD, or Master's degree and 4+ years of science, technology, engineering or related field experience
  • Experience building machine learning models or developing algorithms for business application
  • 1+ years of programming in Java, C++, Python or related language experience
  • Experience in standard machine-learning and statistical modeling tools and techniques (e.g. random forests, gradient-boosted regression, LASSO, logistic regression)

Responsibilities

  • Design and develop machine learning, forecasting, and other prediction models that enhance our optimization and planning systems.
  • Build models and algorithms from prototype to production-level systems.
  • Translate ambiguous business problems into modeling approaches, and drive the technical design with product, engineering, and operations partners.
  • Influence key business decisions through rigorous modeling and analysis.
  • Communicate results and recommendations to scientific and business audiences.

Skills

ML model development
Algorithms
Java
C++
Python

Education

PhD or Master's with 4+ years experience

Job description

Amazon's Middle Mile Surface Research Science seeks an Applied Scientist to invent and build machine learning models that improve how Amazon plans and operates its transportation network.

You will design and deploy forecasting and prediction models, tackle trailer imbalance forecasting, and work with product, engineering, and operations partners to deliver results that impact billions in decisions and enhance the delivery experience for customers.

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