Ops Data Scientist: Causal AI & Forecasting Leader

Amazon Science; Bellevue (WA); On-site; USD 108,000 - 160,000; Full time

Benefits offered by this job

Health insurance

RSUs

401(k) matching

Paid time off

Job summary

Amazon Science in Bellevue, WA, seeks a Data Scientist to drive modeling efforts for optimization of network operations and warehouse processes. You will integrate with business stakeholders and leverage generative AI to build smarter solutions for customers.

You will own project scoping, data enablement, and model development, interfacing with Operations and Finance teams. Strong communication across technical and non-technical stakeholders is essential.

Qualifications

• 1+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
• 2+ years of data/research scientist, statistician or quantitative analyst in an internet-based company with complex and big data sources experience
• Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)

Responsibilities

• Interfacing with stakeholders to understand business problems and translating these into high and low-level design documents.
• Building machine learning, optimization, and causal inference models that target business-specific challenges.
• Sourcing, cleaning, and analyzing large and complex data sets associated with warehouse operations to provide business-critical insights at scale.
• Leveraging AI-based solutions to drive development and provide nuanced insights into model outcomes.

Skills

SQL

Python

R/SAS/Matlab

Education

Master's in STEM

PhD in STEM

Job description

Amazon Science in Bellevue, WA, seeks a Data Scientist to drive modeling efforts for optimization of network operations and warehouse processes. You will integrate with business stakeholders and leverage generative AI to build smarter solutions for customers.

You will own project scoping, data enablement, and model development, interfacing with Operations and Finance teams. Strong communication across technical and non-technical stakeholders is essential.