Senior Data Scientist III, Community Intelligence Science & Engineering

Amazon Science; Bellevue (WA); In loco; USD 159.000 - 215.000; Tempo pieno

Descrizione del lavoro

Amazon Science is seeking a Senior Data Scientist in Bellevue, WA to lead production ML forecasting, NLP/GenAI applications, and scalable analytics platforms. You will partner with product teams and engineers to translate research into practical, scalable solutions that influence operations across Last Mile, Middle Mile, and WW Ops teams.

You will deploy multi-modal data pipelines, mentor junior scientists, and contribute to publications, while collaborating with economists, software developers,

Competenze

• 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

Mansioni

• 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

Conoscenze

SQL

Python

Statistical modeling

AWS

Collaborative

Strumenti

SageMaker

EMR

Lambda

Kinesis

Glue

Descrizione del lavoro

Description

Amazon's Community Intelligence Science & Engineering team operates at the intersection of computational social science, artificial intelligence, and operational excellence. We analyze how Amazon's presence impacts local communities and embed those insights into core operational models. You'll work at the forefront of applied AI and causal inference, building systems that influence decisions affecting thousands of communities daily.

This role offers a unique opportunity to shape how the world's most customer-centric company builds sustainable relationships with the communities we serve. A successful Data Scientist on our team demonstrates exceptional scientific rigor combined with pragmatic execution. You'll balance breakthrough research with production deployment, collaborate across multiple science organizations, and translate complex analytical findings into actionable insights that influence senior leadership strategy.

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.

Key Job Responsibilities

• 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

A Day in the Life

Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment.

The benefits that generally apply to regular, full-time employees include:

• Medical, Dental, and Vision Coverage
• Maternity and Parental Leave Options
• Paid Time Off (PTO)
• 401(k) Plan

About The Team

Amazon Community Operations (CommOps) works to anticipate our communities’ needs and build positive net impact anywhere we operate. From Operational Excellence to Community Outreach, Community Operations is defining what it means to be a positive presence in the community. This is a fast-paced, start-up environment where creative problem solving, operational excellence, and building relationships are the core of our day-to-day work.

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
• Knowledge of AWS tech stack (e.g., AWS Redshift, S3, EC2, Glue)
• Experience working with scientists, economists, software developers, or product managers

Preferred Qualifications

• 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

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Base Salary Range

USA, NY, New York - 175,100.00 - 236,900.00 USD annually

USA, TN, Nashville - 151,200.00 - 204,600.00 USD annually

USA, VA, Arlington - 159,200.00 - 215,300.00 USD annually

USA, WA, Bellevue - 159,200.00 - 215,300.00 USD annually

Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location.