Applied ML Scientist: Transport Optimization

Socket.dev; Bellevue (WA); On-site; USD 143,000 - 193,000; Full time

Job summary

Amazon is seeking an Applied Scientist to design and develop machine learning models for optimizing its transportation network in the Middle Mile. You will invent forecasting models for trailer imbalance and safety stock, owning prediction models and expanding scope over time to influence billions of dollars in decisions.

You will translate complex business problems into modeling approaches, collaborate with product, engineering, and operations teams, and communicate results to both scientific

Qualifications

• PhD or Master’s degree in a related field.
• Experience building machine learning models or developing algorithms for business applications.
• 1+ years of programming in Java, C++, Python or related language.
• Experience with standard ML 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 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

Machine learning

Programming (Java/C++/Python)

Statistical modeling

Education

PhD or Master’s degree in related field

4+ years in science/tech/engineering or related field

Job description

Amazon is seeking an Applied Scientist to design and develop machine learning models for optimizing its transportation network in the Middle Mile. You will invent forecasting models for trailer imbalance and safety stock, owning prediction models and expanding scope over time to influence billions of dollars in decisions.

You will translate complex business problems into modeling approaches, collaborate with product, engineering, and operations teams, and communicate results to both scientific