Applied Scientist II, Sustainability Science and Innovation

Applied Scientist II, Sustainability Science and Innovation

Job : | Services LLC

Join us at Amazon's sustainability initiatives to work on environmental and social advancements that support Amazon's long‑term worldwide sustainability strategy. At Amazon, we're working to be the most customer‑centric company on earth. To get there, we need exceptionally talented, bright, and driven people.

The Worldwide Sustainability organization capitalizes on Amazon’s scale and speed to build a more resilient and sustainable company. We manage our social and environmental impacts globally, and drive solutions that enable customers, businesses, and the world to become more sustainable.

Sustainability Science and Innovation is a multi‑disciplinary team within Worldwide Sustainability combining science, analytics, economics, statistics, machine learning, product development, and engineering expertise. We use data across the sustainability imperatives (carbon, water, waste, biodiversity, environmental risk and more) and these skills and capabilities to identify, develop, experiment, and scale scientific solutions and innovations necessary to help partners solve sustainability needs and goals.

The Sustainability Science and Innovation team is looking for an Applied Scientist II to collaborate closely with Economists and Environmental Scientists to build the AI/ML foundation of the future. You will define modeling strategies and implement tooling to identify, ingest, harmonize, store, and maintain strategic models and data from internal and external sources. These models and datasets must cover a wide range of topics in emerging areas and applications of AI for sustainability and support Amazon‑wide sustainability initiatives such as carbon foot printing, climate risk monitoring, and supply‑chain social responsibility.

Key

job responsibilities

• Implement and maintain data and AI/ML infrastructure to support large and complex data sets, ensuring high performance, availability, and integrity.
• Identify and solve data needs for Gen AI and benchmarking tasks across the sustainability domain.
• Develop and optimize robust data pipelines for internal data sources such as Product Lifecycle Management tools, Product Details (images, text, structured data), Inventory Management Platforms, and financial systems.
• Implement web‑scale data collection for images, text, and structured data across locations and sustainability domains.
• Develop comprehensive monitoring, alarming, and data quality controls for all data pipelines.
• Partner with Scientists and Software Engineers to create data collection strategy and ML Ops best practices.

Basic qualifications

• 3+ years of building models for business applications.
• PhD or Master’s degree and 4+ years of experience in computer science, electrical engineering, machine learning or related field.
• Experience in patents or publications at top‑tier peer‑reviewed conferences or journals.
• Programming experience in Java, C++, Python or related language.
• Experience in algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, or high‑performance computing.

Preferred qualifications

• Experience using Unix/Linux.
• Experience in professional software development.

Equal Opportunity Employer

:

Amazon is an equal‑opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. If you have a disability and need a workplace accommodation, please visit (Use the "Apply for this Job" box below). for more information.

Benefits

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Amazon offers comprehensive benefits including health, dental, vision, prescription, life insurance, employee assistance program, mental health support, medical advice lines, flexible spending accounts, adoption and surrogacy reimbursement, 401(k) matching, paid time off, and parental leave. For more details, visit .

Salary range

: – USD annually (USA, Washington, Seattle).

Location

:

Seattle, Washington, USA.

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