Data Scientist, LM Planning, LM Science & Analytics Automation (Fulfillment & Operations)

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

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Parental leave

Job summary

Amazon Last Mile Strategic Planning seeks a Data Scientist to design and implement optimization solutions for the Delivery Network Topology, partnering with the scientific community and technical teams to improve customer experience and reduce cost to serve. You will translate complex analyses into business-friendly narratives and influence leadership decisions.

You will also mentor teammates, drive high-impact projects, and produce clear design and technical documentation while operating in a

Qualifications

• 2+ years data scientist experience.
• 3+ years SQL or statistical software experience.
• 3+ years ML/statistical modeling and data analysis.
• 1+ years guiding researchers.

Responsibilities

• Design mathematical, statistical and optimization models to optimize Delivery Network Topology.
• Manage several high-impact projects simultaneously.
• Collaborate with business and technical stakeholders to define opportunities.
• Communicate data-driven insights to diverse stakeholders.
• Leverage LLMs to improve explainability and engagement.
• Define measurement frameworks for optimization solutions.

Skills

Data science

SQL

Python

Machine learning

Leadership

Communication

Education

Master's degree in STEM

PhD preferred

Tools

AWS

R/SAS

Job description

Data Scientist, LM Planning, LM Science & Analytics Automation

Job ID: 10510852 | Amazon.com Services LLC

Have you wondered at the speed at which your Amazon purchase arrived at your door, in that box with a smile? wondered where it came from and how much it cost Amazon to deliver it to you?

Amazon Last Mile Strategic Planning is looking for Sr. Data Scientists, developing solutions to optimize our delivery network topology, strategically maximizing Customer Experience and minimizing cost to serve and increase speed.

You will partner with the Scientific community to help design optimization and strategy. You will also collaborate with technical teams developing automated tools for network flow and execution systems. You will work directly with business leadership and operational stakeholders to influence their strategy and gather inputs to solve problems.

To be successful in the role, you will need deep analytical skills and a strong scientific background. The role also requires excellent communication skills, translating technical contents to business friendly narrative. Ability to influence across business functions at different levels, including your own team.

You will work in a fast-paced environment that requires you to be detail-oriented and comfortable in working with data, science, business and technical teams.

Key job responsibilities

• Design and develop mathematical, statistical and optimization models to optimize Delivery Network Topology design..
• Manage several, high impact projects simultaneously
• Consult and collaborate with business and technical stakeholders across multiple teams to define new opportunities to optimize Delivery Network Topology
• Communicate data-driven insights and recommendations to diverse stakeholders through technical and/or business papers
• Leverage LLMs to improve explainability of optimization and drive engagement from volume planning, demand planning stakeholders
• Define measurement frameworks for optimization solutions where no prior art exists and own the scientific framework for ‘Topology Plans’ multi-contact journey
• Choose the right methods (statistical, causal, ML, LLM, hybrid) for each problem and justify trade-offs. Drive excellence in evaluation: ground-truth construction with Quality auditors, human audits, precision/recall, drift, calibration, bias, safety, and cost
• Design driver-analysis and bridging methods explaining KPI movement (WoW, MoM, YoY, vs OP2) across dimensions for "why"
• Partner with teams in productionizing; Own AWS tech stack compliancy (Shepherd risk, App Security red-certification, Kale, Legal, Threat Models, for scientific assets)
• Mentor team members; provide promotion assessments; contribute hiring at DS II and DS III. Represent LM Planning in the broader Amazon Data Science community
• Produce design and technical documentation

A day in the life

• Review current solutions, assumptions and question the status quo to find improvements.
• Drive technical partners adopt improvements, to increase coding velocity, accuracy, quality of scientific solutions. Research for reusable tools/techniques and translate adopting to

About the team

Last Mile is the final mile of Amazon purchase. We- LM Strategic Planning ‘design and plan the Delivery Station Network’. LM network continues to grow multi-fold in North America, AMET, Emerging Market countries, delivering better customer experience and speed to customers. This growth will help Amazon gain most of distribution network share, in every country across the world. LM Strategic Planning-Science Analytics & Automation provides foundational solutions for network expansion roadmap that looks a 1-5 years horizon.

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
• 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
• Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)
• Experience applying theoretical models in an applied environment

Preferred Qualifications

• 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 defining and creating benchmarks for assessing GenAI model performance
• Experience applying quantitative analysis to solve business problems and making data-driven business decisions
• Experience effectively communicating complex concepts through written and verbal communication

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

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Veterans, military spouses, and people with disabilities are encouraged to apply.