Data Scientist , AMXL Worldwide Science

Amazon.com, Inc.
Bellevue, WA, United States
4 days ago
Apply on www.jobmonkeyjobs.com
Prepare application

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience required
1 year minimum
Compensation
$136,000.0 - $184,000.0
Working hours
Regular working hours

Tech stack

Data Analysis Query Languages Perl (Programming Language) R (Programming Language) Python (Programming Language) MATLAB Machine Learning Mathematical Software Routing Operational Data Store SAS (Software) SQL Databases
+6 more
Scripting Feature Engineering Data Ingestion Data Analytics Machine Learning Operations Network Optimization

Job description

Are you passionate about applying machine learning, time series forecasting, and operations research to transform the delivery of heavy and bulky items for Amazon customers? Are you excited about working with large-scale operational data and developing models that drive real business impact? If so, the Amazon Extra Large (AMXL) Science team may be the right fit for you. AMXL is Amazon’s specialized business for delivering heavy and bulky items - appliances, furniture, fitness equipment, and mattresses - with a premium customer experience that includes room-of-choice delivery, at-home installations, and assembly services. In this role, you will leverage large-scale operational data to develop and deploy predictive models and optimization solutions that solve real-world logistics and fulfillment challenges, partnering closely with scientists, engineers, and business stakeholders.

Key job responsibilities

Apply machine learning, statistical modeling, time series analysis, and operations research techniques to build solutions for delivery routing, capacity planning, demand forecasting, workforce scheduling, and network optimization

Analyze large-scale historical and real-time operational data to surface efficiency patterns, bottlenecks, and emerging trends across the AMXL network

Develop, validate, and deploy models that improve cost-to-serve and customer experience

Partner with cross-functional teams to implement data-driven strategies and measure impact

Build scalable, automated pipelines for data ingestion, feature engineering, model training, and validation

Monitor deployed model performance and communicate results through clear reporting on key operational and business metrics

A day in the life

You’ll be part of a small, collaborative team of scientists who move fast and care deeply about the problems they solve. A typical week might involve whiteboarding a new forecasting approach with a senior scientist, partnering with engineers to push a model into production, deep-diving into operational data to understand why a metric moved, or presenting your findings to business leaders who will act on them. The work is high-visibility and high-impact. The models you build will directly influence how millions of heavy and bulky items reach customers.

About the team

The AMXL Science team is a worldwide group of data scientists, applied scientists, and product managers solving Amazon’s most complex heavy bulky supply chain challenges. We build forecasting models, capacity planning systems, and optimization tools that directly impact millions of customer deliveries. Our culture values scientific rigor, measurable business impact, and clear communication. We start with baselines, earn complexity, and partner closely with operations to ensure our work drives real decisions. You’ll tackle problems where logistics constraints demand creative, data-driven solutions - and see your models shape labor planning, routing, and customer experience at scale.

Requirements

Master’s degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)

  • 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
  • 1+ years of guiding and coaching a group of researchers experience
  • 1+ years of working with or evaluating AI systems experience
  • 1+ years of creating or contributing to mathematical textbooks, research papers, or educational content experience
  • Experience applying theoretical models in an applied environment, Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)
  • Knowledge of machine learning concepts and their application to reasoning and problem-solving
  • Experience in Python, Perl, or another scripting language
  • Experience in a ML or data scientist role with a large technology company
  • Experience in defining and creating benchmarks for assessing GenAI model performance
  • Experience working on multi-team, cross-disciplinary projects
  • Experience applying quantitative analysis to solve business problems and making data-driven business decisions
  • Experience effectively communicating complex concepts through written and verbal communication

Benefits & conditions

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

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on www.jobmonkeyjobs.com
Prepare application

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

3:23 min

Exploring specialized career paths within the data science ecosystem

Julian Joseph · LIVE

1:04 min

Introduction to Bitcoin script parsing tools

Steve Shadders · LIVE

2:04 min

Enhancing network privacy with routing fees and onion routing

Andreas M Antonopoulos · LIVE

2:40 min

Motivations for transitioning legacy MATLAB repositories to Python

Michael Niebisch Michael Niebisch · World Congress 2024

3:03 min

Career evolution in data engineering and AI platforms

Maria Apazoglou · Coffee With Developers

1:53 min

Evaluating traditional scripting languages for modern development tasks

Jens Knipper Jens Knipper · Europe 2026 Virtual

Videos

See all

Related articles

See all