Senior Data Scientist, Intelligence & Industrialization

Job Description

Have you ever wondered how Amazon designs and builds its vast transportation and supply chain network? Do you get excited about optimizing global supply chain operations to reduce costs and enhance efficiency? If you thrive in a fast-paced environment and are eager to make a significant impact on a global scale, we want to hear from you!

We are the Intelligence & Industrialization (I&I) team within the Global Supply Chain and Transportation Procurement/ Amazon Customs & Trade (GSCTP/ ACT) organization, at the forefront of 3P transportation logistics procurement and customs & trade operations. We are seeking an experienced and talented data scientist passionate about applying science and machine learning techniques to uncover actionable insights for business decision-making. Examples of these decisions include configuring contractual stipulations, negotiating optimal terms with vendors, and minimizing trade penalty risks and operational delays in customs clearance.

Key Responsibilities

• Work closely with business stakeholders to identify data science use cases, build consensus on project priorities based on data availability, science applicability, implementation challenges, and business impact.
• Lead large data science projects with significant business impact, requiring expertise in both business and technical domains.
• Conduct advanced statistical analyses to uncover causal and other relationships among business metrics and operational characteristics.
• Design and develop robust forecasting models for freight rates, customer demand, and transportation capacity across various dimensions such as geography and mode.
• Build and implement robust ML models for customer segmentation, profitability maximization, performance outlier identification, and risk prediction.
• Leverage state-of-the-art LLM models to build AI tools that reduce manual processes and increase business productivity, such as extracting key terms from vendor contracts, answering SOP and business review questions, and writing narratives and executive summaries.
• Educate non-technical business audience on complex modeling concepts, and explain modeling results, implications, and performance in an accessible manner.
• Collaborate with BIEs, DEs, and other scientists to design and implement end-to-end software solutions powered by science.
• Coach junior scientists and mentor fellow data team members in data science best practices, methodologies, techniques, and trends.

About The Team

The Intelligence & Industrialization (I&I) Team is a functional data analytics sub team embedded across GSCTP & ACT.

Global Supply Chain and Transportation Procurement (GSCTP) is an organization under worldwide operations that manages over 100 third-party supply chain and transportation service providers for Amazon; holding strategic relationships with major providers across modes of transportation, and responsible for an annual spend in excess of $22B. GSCTP’s mission is to secure capacity from third-party providers, increase cost efficiencies of the business, expand supplier capabilities, and improve the quality of our products and services.

Amazon Customs & Trade (ACT) is an expanding business unit under worldwide operations for Customs Brokerage services. Customs brokerage involves the coordination of a complex network of sellers, shippers, logistics service providers (LSP), compliance, and government authorities to facilitate clearance of goods for cross-border transportation. Timely submission of documents and coordination with customs agents to ensure hassle free clearance of shipments is a crucial step in the logistics process to ensure on-time delivery of products to our customers.

Basic Qualifications

• 5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
• 4+ years of data scientist experience
• Experience with statistical models e.g. multinomial logistic regression
• Master's degree

Preferred Qualifications

• 3+ years of data visualization using AWS QuickSight, Tableau, R Shiny, etc. experience
• Experience managing data pipelines
• Experience as a leader and mentor on a data science team
• Experience working with data engineers and business intelligence engineers collaboratively
• Knowledge of AWS tech stack (e.g., AWS Redshift, S3, EC2, Glue)

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.