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# Senior Data Scientist III, Community Intelligence Science & Engineering

- **Company:** Amazon.com, Inc.
- **Location:** New York, NY, United States
- **Experience:** Expert
- **Salary:** $151,200.0 - $236,900.0
- **Contract:** Temporary contract
- **Skills:** Amazon Web Services, Amazon Elastic Compute Cloud, Amazon S3, Query Languages, R (Programming Language), Graph Database, Information Extraction, Python (Programming Language), Logistic Regression, MATLAB, Mathematical Software, SAS (Software), Sentiment Analysis, SQL Databases, Unstructured Data, Scripting, Large Language Models, Generative AI, Data Pipelines, Amazon Redshift
- **Published:** October 6, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=c10377bc1accdce5

## About the Role

* 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
 * Knowledge of AWS tech stack (e.g., AWS Redshift, S3, EC2, Glue)
 * Experience working with scientists, economists, software developers, or product managers, * Experience with data scripting languages (e.g., SQL, Python, R, or equivalent) or statistical/mathematical software (e.g., R, SAS, Matlab, or equivalent)
 * Experience managing data pipelines
 * Experience as a leader and mentor on a data science team
 * Experience documenting modeling for technical and business leaders
 * Experience using AI-assisted development tools in academic or professional settings
 * Experience contributing to publications at top-tier peer-reviewed conferences or journals

## Description

As a Senior Data Scientist, you will partner with product teams, scientists, and technical leaders across Last Mile, Middle Mile, WW Ops Security, WW Real Estate, and other organizations to identify opportunities where community intelligence creates multiplicative business impact., * Design and deploy production ML forecasting systems with extended prediction horizons using multi-modal data sources

 * Build and scale AI-powered analytics platforms that process large volumes of unstructured data from diverse sources including social media, traditional media, and internal systems
 * Collaborate with operational science teams to integrate analytical insights and predictive signals into existing operational models and decision-making systems
 * Build automated causal discovery systems leveraging knowledge graphs, LLMs, and document understanding to uncover relationships between business actions and outcomes
 * Develop NLP and GenAI applications including event detection, sentiment analysis, cross-platform clustering, and multilingual insight synthesis
 * Partner with engineering teams to productionize models using AWS services (SageMaker, EMR, Lambda, Kinesis, Glue) with clear POC-to-production handoff criteria
 * Mentor junior scientists and contribute to building a research culture that balances high-risk, high-reward innovation with reliable product delivery
 * Author internal and externally-facing scientific publications and technical documents