Description

Join us at the cutting edge of Amazon's sustainability initiatives to work on environmental and social advancements to 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 to build a more resilient and sustainable company. We manage our social and environmental impacts globally, driving solutions that enable our customers, businesses, and the world around us to become more sustainable.

Sustainability Science and Innovation (SSI) is a multi-disciplinary team within the WW Sustainability organization that combines science, analytics, economics, statistics, machine learning, product development, and engineering expertise. We use this expertise and skills to identify, develop and evaluate the science and innovations necessary for Amazon, customers and partners to meet their long-term sustainability goals and commitments.

We are seeking an experienced Senior Applied Scientist to play a key role in our work to achieve our long-term sustainability and climate commitments. In this role, you will leverage your breadth of expertise in data science methodologies, statistical modeling, and scientific programming to analyze complex datasets, build scientific tools, and inform sustainability strategies across carbon, waste, and water management.

The successful applicant will lead by example, pioneering science-vetted data-driven approaches, and working collaboratively to implement strategies that align with Amazon’s long-term sustainability vision.

You will be at the forefront of exploring and resolving complex sustainability issues, bringing innovative ideas to the table, and making meaningful contributions to projects across SSI’s portfolio. This role not only demands technical expertise but also a strategic mindset and the agility to adapt to evolving sustainability challenges through self-driven learning and exploration.

Key job responsibilities

• Own the design and development of scientific scripts to solve complex and ambiguous problems, and extract strategic learnings from large datasets.

• Effectively influence stakeholders across partner teams through strong communication, and high-quality technical artifacts.

• Professionally communicate your work to senior business leaders and the broader science community.

• Work closely with software engineering teams to implement your scientific models.

• Lead early-stage strategic sustainability initiatives and effectively learn from, collaborate with, and influence stakeholders to scale-up high-value initiatives.

About the team

Diverse Experiences:

World Wide Sustainability (WWS) values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.

Inclusive Team Culture:

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.

Mentorship & Career Growth:

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.

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.

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

San Francisco, CA, USA

Basic Qualifications

• 3+ years of investigating the feasibility of applying scientific principles and concepts to business problems and products experience

• PhD, or Master's degree and 5+ years of quantitative field research experience

• Experience with big data technologies such as AWS, Hadoop, Spark, Pig, Hive etc.

• Experience communicating qualitative research methods and findings to non-qualitative researchers

Preferred Qualifications

• Experience converting research studies into tangible real-world changes

• Experience with discrete and continuous optimization methodologies and algorithms

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 https://www.amazon.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 $136,000/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 https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.