Applied Scientist II, SCOT-Optimal Sourcing Systems, Buying Science Team
Company websiteamazon.com (Amazon, opens in new tab)
Base salary $142,800 to $193,200
Employer-published annual base salary, USD. Advertised base range in Bellevue, WA
You apply on the employer's own site. Six Figure Work does not handle applications.
- LocationBellevue, WA
- WorkplaceWorkplace not stated
- Status at last checkSource accepting applications when checked
- Last checked (1 h ago) · observed since
About this job
Amazon is looking for an Applied Scientist to help build the next generation of sourcing and vendor experience systems. The Optimal Sourcing Systems (OSS) owns the optimization of inventory sourcing and the orchestration of inbound flows from vendors worldwide. We source inventory from thousands of vendors for millions of products globally while orchestrating the inbound flow for billions of units.
Our goals are to increase reliable access to supply, improve supply chain-driven vendor experience, and reduce end-to-end supply chain costs, all in service of maximizing Long-Term Free Cash Flow (LTFCF) for Amazon.
As an Applied Scientist, you will work with software engineers, product managers, and business teams to understand the business problems and requirements, distill that understanding to crisply define the problem, and design and develop innovative solutions to address them.
Our team is highly cross-functional and employs a wide array of scientific tools and techniques to solve key challenges, including optimization, causal inference, and machine learning/deep learning. Some critical research areas in our space include modeling buying decisions under high uncertainty, vendors' behavior and incentives, supply risk and enhancing visibility and reliability of inbound signals.
Key job responsibilities
- Set the scientific strategic vision for the team. Lead problem decomposition and roadmap development.
- Identify and frame research challenges in ambiguous problem areas; invent novel methodologies to address them. Distinguish between problems requiring novel solutions versus those addressable with existing approaches.
- Exercise sound judgment to prioritize between short-term vs. long-term and business vs. technology needs.
- Set an example with exemplary scientific analyses; maintainable, well-tested code; and simple, effective solutions.
- Drive the design of scientifically-complex software solutions, personally writing critical-path code that embodies scientific novelty. Deploy novel models into production with a track record of impactful delivery.
- Develop reusable science components that resolve architecture deficiencies; set standards and drive adoption of state-of-the-art techniques.
- Influence team business and engineering strategies. - Communicate effectively with stakeholders to drive alignment and build consensus.
- Foster collaborations between scientists across Amazon researching similar problems. Proactively resolve endemic issues where the team's technologies bottleneck other teams.
- Actively engage in the development of others, both within and outside the team.
- Participate in the science hiring process and engage with the broader scientific community through publications, presentations, and patents.
Basic Qualifications
- PhD in operations research, applied mathematics, theoretical computer science, or equivalent, or Master's degree and 4+ years of machine learning, statistical modeling, data mining, and analytics techniques experience
- Knowledge of supply chain management concepts - forecasting, planning, sourcing, optimization and logistics or equivalent
- Experience building and deploying machine learning or optimization models for business applications at scale
- Proficiency in Python with experience developing production-quality scientific software
- Technical depth in one or more of: mathematical optimization, causal inference, sequential decision-making (RL/MDP), or stochastic modeling
Preferred Qualifications
- Publication record in operations research, machine learning, or a related quantitative field
- Experience with optimization solvers (e.g., Gurobi, OR-Tools) or reinforcement learning frameworks (e.g., RLlib, Stable Baselines)
- Experience with deep learning frameworks (e.g., PyTorch, TensorFlow)
- Experience designing and analyzing experiments in operational or supply chain settings
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 - 142,800.00 - 193,200.00 USD annually
Source: Amazon · View original posting (opens in new tab)
Pay in context
This role's base floor ($142,800) is above 28% of the 357 Data & ML roles in Washington listed on this site; 69 others list the same floor. Their median floor is $143,700; the middle half runs from $136,000 to $168,100.
Only jobs on this site count, and each one publishes a base salary of $100,000 or more, so this compares six-figure jobs with each other, not with the whole market. Computed Nov 8, 2026.
This listingApplied Scientist II, SCOT-Optimal Sourcing Systems, Buying Science Team$142,800 to $193,200
Design Technologist II, Elevated Shopping Experience$145,000 to $196,100
Senior Industrial Designer$145,200 to $196,500
Data Center Area Operations Manager$145,400 to $254,500
MDD DCO Cluster Manager$145,400 to $254,500
Data Center Area Operations Manager, Data Center Operations$145,400 to $254,500
Data Center Operations Cluster Manager$145,400 to $254,500
Chart as a table
| Role | Published base |
|---|---|
| Applied Scientist II, SCOT-Optimal Sourcing Systems, Buying Science Team (this listing) | $142,800 - $193,200 |
| Design Technologist II, Elevated Shopping Experience | $145,000 - $196,100 |
| Senior Industrial Designer | $145,200 - $196,500 |
| Data Center Area Operations Manager | $145,400 - $254,500 |
| MDD DCO Cluster Manager | $145,400 - $254,500 |
| Data Center Area Operations Manager, Data Center Operations | $145,400 - $254,500 |
| Data Center Operations Cluster Manager | $145,400 - $254,500 |
Observed changes
- First observed on the employer's board
- Began meeting the published-salary criteria
- Observed since
- Employer-stated posting date
- 2026-07-07
Where this pay comes from
Location as the employer wrote it: US, WA, Bellevue
USA, WA, Bellevue - 142,800.00 - 193,200.00 USD annually
- Method
- Employer text, read with fixed rules and re-verified
- Checked
- Rule set
- us-base-v2
The pay passage appears in the employer's own job text. Fixed, deterministic rules located it, and the passage below was checked against the stored copy of the posting.
What we verified
- The pay figures come from the employer's own listing, quoted exactly above.
- The pay is an annual base salary in US dollars with a minimum of at least $100,000.
- The role was publicly listed on the employer's job board when last checked.
We do not verify what the employer will actually offer, whether the employer is still recruiting for the role, or anything beyond what the employer published. Full methodology.
