AmazonApplied Scientist II, SCOT-Optimal Sourcing Systems, Buying Science Team
Amazon is hiring an Applied Scientist II, SCOT-Optimal Sourcing Systems, Buying Science Team in Bellevue, United States. It pays $143k-$193k a year and Level rates it ; you can apply on Amazon.
Level's read on this job
- Builds AI ●●●● is how Level rates this applied scientist role: the job is building AI systems.
- Tools and skills the posting cites include PyTorch, TensorFlow and Python.
- Level classifies it as a senior role.
- Level lists 20,000+ other open roles at Amazon.
AI in this role
Build next-generation machine learning and optimization systems for Amazon's global supply chain and sourcing.
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
How we rate this
Applied Scientist II, SCOT-Optimal Sourcing Systems, Buying Science Team at Amazon rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Pay
- This job starts at
- $143k
- Typical applied scientist job
- $172k
This posting starts 17% below the typical applied scientist job. See applied scientist jobs
Questions you could be asked
- Tell me about a project where machine learning was part of your work. What did you do?
- Tell me about a project where deep learning was part of your work. What did you do?
- Tell me about a project where optimization was part of your work. What did you do?
- Tell me about a project where causal inference was part of your work. What did you do?
- Walk me through how you've used PyTorch in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: Machine learning, Deep learning, Optimization, Causal Inference, and PyTorch. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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