Senior Applied Scientist, WW Sustainability_

Seattle

Description

Join us at the cutting edge of Amazon's sustainability initiatives to work on environmental and social advancements and 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 (WWS) organization capitalizes on Amazon’s scale, speed, and ability to build, invent and simplify, a more resilient and sustainable company. We manage our social and environmental impacts globally, and drive solutions that enable our customers, businesses, and the world to become more sustainable.

Sustainability Science and Innovation (SSI) is a multi-disciplinary team within WW 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 the scientific solutions and innovations necessary for Amazon, customers and partners to help them solve their hardest unmet and evolving sustainability needs and goals.

The Sustainability Science team is looking for an experienced Applied Scientist to join our team. The ideal candidate will have strong science breadth and experience in Generative AI to computer vision to NLP. This candidate will also possess excellent communication skills to drive consensus across multiple stakeholders as well as the ability to thrive in ambiguous problem spaces and wear many hats.

This is a unique opportunity for someone who wants to come show their passion for sustainability, solving customer problems, and working on a high-performing team that includes many world-leading experts in their fields.

Key job responsibilities

- Design, implement, test, deploy, and maintain innovative data and machine learning solutions to accelerate our business.

- Create experiments and prototype implementations of new learning algorithms and prediction techniques

- Collaborate with scientists, engineers, product managers, and stakeholders to design and implement software solutions for science problems

- Use machine learning best practices to ensure a high standard of quality for all of the team deliverables

- Lead the early investigative / inception phase of strategic sustainability initiatives and effectively influence, negotiate, and communicate with stakeholders to enable hand off of those projects for implementation.

About the team

Inclusive Team Culture:

Here at Amazon, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.

Work/Life Balance:

We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve.

Mentorship and Career Growth:

We have a career path for you no matter what stage you’re in when you start here. We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

We are open to hiring candidates to work out of one of the following locations:

Arlington, VA, USA | San Francisco, CA, USA | Seattle, WA, USA

Basic Qualifications

- 3+ years of building machine learning models for business application experience

- Experience with neural deep learning methods and machine learning

- PhD, or Master's degree and 5+ years of applied research experience

- Experience programming in Java, C++, Python or related language

Preferred Qualifications

- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.

- Experience with popular deep learning frameworks such as MxNet and Tensor Flow.

- Experience with large scale distributed systems such as Hadoop, Spark etc.

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit mazon.jobs/en/disability/us.

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit boutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.