Pay
$118K–$195K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 3,828 postings in the last year. Stated ranges, not salaries paid.
Data Scientist , Amazon Transportation Services (NEST)
Bellevue, Washington, USA
Actively hiring, first seen by us 5 hours ago- Pay
Pay amount needs review — pay source
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. 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. USA, WA, Bellevue - 136,000.00 - 184,000.00 USD annually
Read the full posting- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type in the employer’s posting: full-time
From the employer’s posting
What you’ll work on
Full postingYou will collaborate closely with scientists, engineers, and product managers
From the employer’s posting
Come join the Network Engineering, Scheduling and Technology (NEST) Science team within Amazon Transportation Services. We are looking for a Data Scientist who is equal parts data engineer, visualization architect, and analytical modeler. You will own the end-to-end build process for data-driven solutions: identifying business needs, developing simulation and optimization models, building computationally efficient analytical tools, and narrating results through compelling data storytelling. This is not a dashboard-building role. You will work at the intersection of large-scale data processing, advanced analytics (including simulation and optimization), and data visualization, building tools that allow stakeholders to explore millions of records interactively, uncover patterns in network performance, and make data-driven decisions with confidence. The ideal candidate is a data wizard who thrives on wrangling massive datasets, building predictive and prescriptive models, architecting performant query and aggregation pipelines, and crafting visualizations that communicate complex findings with precision and clarity. You will own the full lifecycle, from problem identification and data extraction through modeling and simulation to production-grade analytical applications that narrate results back to stakeholders. You will collaborate closely with scientists, engineers, and product managers Key job responsibilities - Own the end-to-end analytical lifecycle: identify stakeholder needs, frame problems, build models, and narrate results through data tools and visualizations
Education & alternatives
About the team The Network Engineering, Scheduling, and Technology (NEST) Science Team prototype, build, and productionize mathematical models that reduce transportation cost and improve customer experience in Amazon's Middle Mile network. Equipped with techniques from Operations Research, Machine Learning and Simulation, these models are used to govern scheduling and equipment selection of hundreds of thousands of truck movements, optimize network configurations, determine the transit times between nodes, and simulate network flow under uncertainty for informed decision making. Our core team consists of Applied, Data, and Research Scientists along with technical Product Managers that come from diverse backgrounds. Basic qualifications - 2+ years of data scientist experience - 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience - 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience - Experience applying theoretical models in an applied environment - Experience with big data: processing, filtering, and presenting large quantities (100K to Millions of rows) of data - Bachelor's degree Preferred qualifications - Master's degree - Experience in a ML or data scientist role with a large technology company - Experience with AWS services including S3, Redshift, Sagemaker, EMR, Kinesis, Lambda, and EC2 - Experience in building self-service analytical tools - Proficiency in advanced visualization libraries and frameworks (D3.js, Deck.gl, Plotly, etc.)
- 2+ years of data scientist experience - 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience - 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience - Experience applying theoretical models in an applied environment - Experience with big data: processing, filtering, and presenting large quantities (100K to Millions of rows) of data - Bachelor's degree Preferred qualifications - Master's degree - Experience in a ML or data scientist role with a large technology company - Experience with AWS services including S3, Redshift, Sagemaker, EMR, Kinesis, Lambda, and EC2 - Experience in building self-service analytical tools - Proficiency in advanced visualization libraries and frameworks (D3.js, Deck.gl, Plotly, etc.) Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Posting record
Report an errorActively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Nov 13, 2026today
- Recorded sightings
- 1
- Employer says posted
- Sep 1, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
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From 11,733 similar postings that came down. Coming down is not always a hire.
Amazon is hiring
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Hiring recordSee how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- MATLAB
- Python
- R
- SAS
- Scala
- SQL
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- Redshift
- S3
- SageMaker
- Spark
- Plotly
Where the posting names them
About the team The Network Engineering, Scheduling, and Technology (NEST) Science Team prototype, build, and productionize mathematical models that reduce transportation cost and improve customer experience in Amazon's Middle Mile network. Equipped with techniques from Operations Research, Machine Learning and Simulation, these models are used to govern scheduling and equipment selection of hundreds of thousands of truck movements, optimize network configurations, determine the transit times between nodes, and simulate network flow under uncertainty for informed decision making. Our core team consists of Applied, Data, and Research Scientists along with technical Product Managers that come from diverse backgrounds. Basic qualifications - 2+ years of data scientist experience - 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience - 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience - Experience applying theoretical models in an applied environment - Experience with big data: processing, filtering, and presenting large quantities (100K to Millions of rows) of data - Bachelor's degree Preferred qualifications - Master's degree - Experience in a ML or data scientist role with a large technology company - Experience with AWS services including S3, Redshift, Sagemaker, EMR, Kinesis, Lambda, and EC2 - Experience in building self-service analytical tools - Proficiency in advanced visualization libraries and frameworks (D3.js, Deck.gl, Plotly, etc.)
- Work with large-scale data platforms (Redshift, Spark, S3, Athena) to extract, transform, and model data for analytical consumption - Develop code (Python, SQL, Scala) for data processing, statistical modeling, simulation, and building automated analytical workflows - Collaborate with Applied Scientists, Research Scientists, Software Engineers, and Product Managers to integrate analytical tools into broader planning and decision-support systems
- 2+ years of data scientist experience - 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience - 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience - Experience applying theoretical models in an applied environment - Experience with big data: processing, filtering, and presenting large quantities (100K to Millions of rows) of data - Bachelor's degree Preferred qualifications - Master's degree - Experience in a ML or data scientist role with a large technology company - Experience with AWS services including S3, Redshift, Sagemaker, EMR, Kinesis, Lambda, and EC2 - Experience in building self-service analytical tools - Proficiency in advanced visualization libraries and frameworks (D3.js, Deck.gl, Plotly, etc.) Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
- Build and maintain reusable visualization frameworks and libraries tailored to transportation network data (routing, scheduling, flow, capacity) - Work with large-scale data platforms (Redshift, Spark, S3, Athena) to extract, transform, and model data for analytical consumption - Develop code (Python, SQL, Scala) for data processing, statistical modeling, simulation, and building automated analytical workflows
Your next step
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Demand for Data Scientist roles
New Data Scientist postings at the employers we follow are down 4% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under Data Scientist, by the work the posting describes.
Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.
Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.
Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.
US government figures for data scientists
- Median yearly pay, May 2025
- $120,230
- Expected change, 2025 to 2035
- 34.6% more jobsagainst 3.5% for all jobs
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.
Job description
Have you ever placed an order on Amazon and wondered how it got to you so fast? Behind that speed is a massive transportation network generating billions of data points daily. We need someone who can turn that data into clarity.
Come join the Network Engineering, Scheduling and Technology (NEST) Science team within Amazon Transportation Services. We are looking for a Data Scientist who is equal parts data engineer, visualization architect, and analytical modeler. You will own the end-to-end build process for data-driven solutions: identifying business needs, developing simulation and optimization models, building computationally efficient analytical tools, and narrating results through compelling data storytelling. This is not a dashboard-building role. You will work at the intersection of large-scale data processing, advanced analytics (including simulation and optimization), and data visualization, building tools that allow stakeholders to explore millions of records interactively, uncover patterns in network performance, and make data-driven decisions with confidence.
The ideal candidate is a data wizard who thrives on wrangling massive datasets, building predictive and prescriptive models, architecting performant query and aggregation pipelines, and crafting visualizations that communicate complex findings with precision and clarity. You will own the full lifecycle, from problem identification and data extraction through modeling and simulation to production-grade analytical applications that narrate results back to stakeholders. You will collaborate closely with scientists, engineers, and product managers
Key job responsibilities
- Own the end-to-end analytical lifecycle: identify stakeholder needs, frame problems, build models, and narrate results through data tools and visualizations
- Design and build production-grade analytical tools, BI applications, and interactive data products that enable self-service exploration of very large transportation datasets (billions of records)
- Develop and enhance simulation and optimization models (discrete event simulation, agent-based modeling, mathematical optimization) applied to network planning and transportation operations
- Architect computationally efficient data pipelines and aggregation strategies that support responsive, real-time or near-real-time visualization at scale
- Develop advanced data storytelling artifacts that communicate complex network dynamics, trends, and anomalies to technical and non-technical stakeholders
- Build and maintain reusable visualization frameworks and libraries tailored to transportation network data (routing, scheduling, flow, capacity)
- Work with large-scale data platforms (Redshift, Spark, S3, Athena) to extract, transform, and model data for analytical consumption
- Develop code (Python, SQL, Scala) for data processing, statistical modeling, simulation, and building automated analytical workflows
- Collaborate with Applied Scientists, Research Scientists, Software Engineers, and Product Managers to integrate analytical tools into broader planning and decision-support systems
- Define and implement best practices for data visualization performance, including sampling strategies, level-of-detail rendering, and progressive loading for large datasets
- Communicate findings, methodology, and recommendations through compelling written and verbal presentations to leadership and business customers
About the team
The Network Engineering, Scheduling, and Technology (NEST) Science Team prototype, build, and productionize mathematical models that reduce transportation cost and improve customer experience in Amazon's Middle Mile network. Equipped with techniques from Operations Research, Machine Learning and Simulation, these models are used to govern scheduling and equipment selection of hundreds of thousands of truck movements, optimize network configurations, determine the transit times between nodes, and simulate network flow under uncertainty for informed decision making. Our core team consists of Applied, Data, and Research Scientists along with technical Product Managers that come from diverse backgrounds.
- 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
- Experience applying theoretical models in an applied environment
- Experience with big data: processing, filtering, and presenting large quantities (100K to Millions of rows) of data
- Bachelor's degree
- Experience in a ML or data scientist role with a large technology company
- Experience with AWS services including S3, Redshift, Sagemaker, EMR, Kinesis, Lambda, and EC2
- Experience in building self-service analytical tools
- Proficiency in advanced visualization libraries and frameworks (D3.js, Deck.gl, Plotly, etc.)
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.
USA, WA, Bellevue - 136,000.00 - 184,000.00 USD annually
Come join the Network Engineering, Scheduling and Technology (NEST) Science team within Amazon Transportation Services. We are looking for a Data Scientist who is equal parts data engineer, visualization architect, and analytical modeler. You will own the end-to-end build process for data-driven solutions: identifying business needs, developing simulation and optimization models, building computationally efficient analytical tools, and narrating results through compelling data storytelling. This is not a dashboard-building role. You will work at the intersection of large-scale data processing, advanced analytics (including simulation and optimization), and data visualization, building tools that allow stakeholders to explore millions of records interactively, uncover patterns in network performance, and make data-driven decisions with confidence.
The ideal candidate is a data wizard who thrives on wrangling massive datasets, building predictive and prescriptive models, architecting performant query and aggregation pipelines, and crafting visualizations that communicate complex findings with precision and clarity. You will own the full lifecycle, from problem identification and data extraction through modeling and simulation to production-grade analytical applications that narrate results back to stakeholders. You will collaborate closely with scientists, engineers, and product managers
Key job responsibilities
- Own the end-to-end analytical lifecycle: identify stakeholder needs, frame problems, build models, and narrate results through data tools and visualizations
- Design and build production-grade analytical tools, BI applications, and interactive data products that enable self-service exploration of very large transportation datasets (billions of records)
- Develop and enhance simulation and optimization models (discrete event simulation, agent-based modeling, mathematical optimization) applied to network planning and transportation operations
- Architect computationally efficient data pipelines and aggregation strategies that support responsive, real-time or near-real-time visualization at scale
- Develop advanced data storytelling artifacts that communicate complex network dynamics, trends, and anomalies to technical and non-technical stakeholders
- Build and maintain reusable visualization frameworks and libraries tailored to transportation network data (routing, scheduling, flow, capacity)
- Work with large-scale data platforms (Redshift, Spark, S3, Athena) to extract, transform, and model data for analytical consumption
- Develop code (Python, SQL, Scala) for data processing, statistical modeling, simulation, and building automated analytical workflows
- Collaborate with Applied Scientists, Research Scientists, Software Engineers, and Product Managers to integrate analytical tools into broader planning and decision-support systems
- Define and implement best practices for data visualization performance, including sampling strategies, level-of-detail rendering, and progressive loading for large datasets
- Communicate findings, methodology, and recommendations through compelling written and verbal presentations to leadership and business customers
About the team
The Network Engineering, Scheduling, and Technology (NEST) Science Team prototype, build, and productionize mathematical models that reduce transportation cost and improve customer experience in Amazon's Middle Mile network. Equipped with techniques from Operations Research, Machine Learning and Simulation, these models are used to govern scheduling and equipment selection of hundreds of thousands of truck movements, optimize network configurations, determine the transit times between nodes, and simulate network flow under uncertainty for informed decision making. Our core team consists of Applied, Data, and Research Scientists along with technical Product Managers that come from diverse backgrounds.
Basic qualifications
- 2+ years of data scientist experience- 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
- Experience applying theoretical models in an applied environment
- Experience with big data: processing, filtering, and presenting large quantities (100K to Millions of rows) of data
- Bachelor's degree
Preferred qualifications
- Master's degree- Experience in a ML or data scientist role with a large technology company
- Experience with AWS services including S3, Redshift, Sagemaker, EMR, Kinesis, Lambda, and EC2
- Experience in building self-service analytical tools
- Proficiency in advanced visualization libraries and frameworks (D3.js, Deck.gl, Plotly, etc.)
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.
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. 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.
USA, WA, Bellevue - 136,000.00 - 184,000.00 USD annually
Source details
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Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
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. 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. USA, WA, Bellevue - 136,000.00 - 184,000.00 USD annually
- Location & working pattern
Bellevue, Washington, USA
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.