Applied Scientist, Worldwide Grocery Stores - Data and Science

Amazon Science; Seattle (WA); On-site; USD 136,000 - 184,000; Full time

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Job summary

Amazon is seeking an Applied Scientist to join the S&OP and Supply Chain Science team in Seattle. You will build forecasting models for labor planning across the Grocery Network, collaborating with engineers, product owners, and business stakeholders to drive staffing decisions.

You will work with time-series, Bayesian, and ML approaches, contribute to AI-in-the-loop forecasting, and help deploy scalable forecasting systems in a modern data platform.

Qualifications

• Master's degree or higher in a relevant field such as Engineering, CS, ML, Stats, or Physics.
• Experience building ML models or algorithms for business applications.
• Proficiency in Python with pandas, NumPy, scikit-learn.
• Experience with SQL and large-scale data processing on a platform like Redshift, Spark, or EMR.

Responsibilities

• Develop, evaluate, and deploy components of demand and labor forecasting models with distributional objectives.
• Translate business problems into well-defined scientific solutions with clear objectives and metrics.
• Analyze forecast performance and downstream impact on labor planning and capacity decisions.
• Prototype and evaluate Generative AI approaches in forecasting workflows.
• Partner with engineering teams to produce models and build scalable forecasting systems.
• Monitor deployed models and continuously improve calibration.
• Communicate technical concepts through documentation, presentations, and reviews.
• Contribute to internal scientific community through knowledge sharing and publications.

Skills

Python

ML models

SQL

Time-series forecasting

SageMaker

AWS

Education

Master's degree or above in Engineering, CS, ML, Statistics, Physics, or related fields

Tools

Redshift

Spark

EMR

Job description

Description

Amazon's Worldwide Grocery Stores (WWGS), Data & Science team is seeking an Applied Scientist to join our Sales & Operations Planning (S&OP) and Supply Chain Science team. In this role, you will help build forecasting models that drive labor planning across the Amazon Grocery Network, where forecast misses can lead directly to staffing inefficiencies, higher costs, and degraded customer experience.

Description

Amazon's Worldwide Grocery Stores (WWGS), Data & Science team is seeking an Applied Scientist to join our Sales & Operations Planning (S&OP) and Supply Chain Science team. In this role, you will help build forecasting models that drive labor planning across the Amazon Grocery Network, where forecast misses can lead directly to staffing inefficiencies, higher costs, and degraded customer experience.

You will contribute to the development and deployment of demand and labor forecasting models using Time-series, Bayesian and Structural methods, and Machine Learning. Senior scientists on the team will partner with you to scope problems and review designs, giving you room to build depth in forecasting science and production ML. You will also work directly with engineering partners, product owners, and business stakeholders, so you will see how your models change the decisions they make.

Forecasts directly inform downstream labor and capacity decisions, so understanding how errors affect stakeholders is as important as improving accuracy. You will participate in design and roadmap discussions, communicate clearly with technical and non-technical partners, and develop judgment about the trade-offs in the systems you contribute to.

We are investing in Generative AI to advance forecasting workflows, moving from human-in-the-loop to AI-in-the-loop decision support. Opportunities include automating forecast overrides for known events, identifying persistent bias, and augmenting planner and scientist judgment with agentic tools.

Key job responsibilities

• Develop, evaluate, and deploy components of our demand and labor forecasting models, including statistical time-series, Bayesian, and machine-learning models with distributional objectives, with input and guidance from senior scientists.


• Translate business problems into well‑defined scientific solutions with clear objectives, constraints, and success metrics, partnering with senior scientists on the more ambiguous ones.


• Analyze forecast performance and downstream impact on labor planning and capacity decisions; develop metrics that reflect business outcomes, not only forecast accuracy.


• Prototype and evaluate Generative AI approaches in our forecasting workflows and help productionize the ones that succeed.


• Partner with engineering teams to produce models, contribute to data pipelines, and build scalable, maintainable forecasting systems.


• Monitor deployed models, investigate performance issues, and continuously improve model quality and calibration.


• Communicate technical concepts and recommendations clearly through documentation, presentations, and design reviews with scientists, engineers, product managers, and business leaders.


• Contribute to the internal scientific community through knowledge sharing and, where appropriate, research publications.

Basic Qualifications

• Master's degree or above in Engineering, Computer Science, Machine Learning, Statistics, Physics, or related fields


• Experience building machine learning models or developing algorithms for business application


• Proficiency in Python, including scientific computing and ML libraries (e.g., pandas, NumPy, scikit-learn)


• Experience with SQL and large-scale data processing on a modern data platform (e.g., Redshift, Spark, EMR, or equivalent data warehouse)

Preferred Qualifications

• Experience implementing algorithms using both toolkits and self‑developed code


• Experience with time‑series forecasting or demand planning


• Experience training and deploying models in a cloud environment (e.g., SageMaker, EC2, AWS Batch)


• Publications in 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.

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, Seattle - 136,000.00 - 184,000.00 USD annually