Description

　　The Fulfillment by Amazon (FBA) team is looking for a passionate, curious, and creative Principal Applied Scientist, with expertise in machine learning and a proven record of solving business problems through scalable ML solutions, to join our top-notch cross-domain FBA science team. We want to learn seller behavior, understand seller experience, build automated LLM-based assistant to sellers or an indefinitely patient, infinitely knowledgeable co-pilot, recommend right actions to sellers, design seller policies and incentives, and develop science products and services that empower third-party sellers to grow their businesses. We also predict potentially costly defects that may occur during packing, shipping, receiving and storing the inventory. We aim to prevent such defects before occurring while we are also fulfilling customer demand as quickly and efficiently as possible, in addition to managing returns and reimbursements. To do so, we build and innovate science solutions at the intersection of machine learning, statistics, economics, operations research, and data analytics. As a principal applied scientist, you will propose and deploy solutions that will likely draw from a range of scientific areas such as supervised and unsupervised learning, recommendation systems, advanced statistical modeling, LLMs, transfer learning, and reinforcement learning. This role has high visibility to senior Amazon business leaders and involves working with other scientists, and partnering with engineering and product teams to integrate scientific work into production systems.

　　Key job responsibilities

　　As a senior member of the science team, you will play an integral part in building Amazon's FBA management system with the following technical and leadership responsibilities:

　　• Research and develop automated LLM-based assistant to Sellers - an indefinitely patient, infinitely knowledgeable co-pilot that present growth opportunities, cost-out recommendations to maximize business outcomes for Sellers.

　　• Research and develop machine learning models to solve diverse business problems faced in Seller inventory management systems.

　　• Define a long-term science vision and roadmap for the team, driven fundamentally from our customers' needs, translating those directions into specific plans for research and applied scientists, as well as engineering and product teams.

　　• Drive and execute machine learning projects/products end-to-end: from ideation, analysis, prototyping, development, metrics, and monitoring.

　　• Review and audit modeling processes and results for other scientists, both junior and senior.

　　• Advocate the right ML solutions to business stakeholders, engineering teams, as well as executive level decision makers

　　A day in the life

　　In this role, you will be a technical leader in machine learning with significant scope, impact, and high visibility. Your solutions may lead to billions of dollars impact on either the topline or the bottom line of Amazon third-party seller business. As a senior scientist on the team, you will be involved in every aspect of the process - from idea generation, business analysis and scientific research, through to development and deployment of advanced models - giving you a real sense of ownership. From day one, you will be working with experienced scientists, engineers, and designers who love what they do. You are expected to make decisions about technology, models and methodology choices. You will strive for simplicity, and demonstrate judgment backed by mathematical proof. You will also collaborate with the broader decision and research science community in Amazon to broaden the horizon of your work and mentor engineers and scientists. The successful candidate will have the strong expertise in applying machine learning models in an applied environment and is looking for her/his next opportunity to innovate, build, deliver, and impress. We are seeking someone who wants to lead projects that require innovative thinking and deep technical problem-solving skills to create production-ready machine learning solutions. The candidate will need to be entrepreneurial, wear many hats, and work in a fast-paced, high-energy, highly collaborative environment. We value highly technical people who know their subject matter deeply and are willing to learn new areas. We look for individuals who know how to deliver results and show a desire to develop themselves, their colleagues, and their career.

　　About the team

　　Fulfillment by Amazon (FBA) is a service that allows sellers to outsource order fulfillment to Amazon, allowing sellers to leverage Amazon’s world-class facilities to provide customers Prime delivery promise. Sellers gain access to Prime members worldwide, see their sales lift, and are free to focus their time and resources on what they do best while Amazon manages fulfillment. Over the last several years, sellers have enjoyed strong business growth with FBA shipping more than half of all products offered by Amazon. FBA focuses on helping sellers with automating and optimizing the third-party supply chain. FBA sellers leverage Amazon’s expertise in machine learning, optimization, data analytics, econometrics, and market design to deliver the best inventory management experience to sellers. We work full-stack, from foundational backend systems to future-forward user interfaces. Our culture is centered on rapid prototyping, rigorous experimentation, and data-driven decision-making.

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

　　Bellevue, WA, USA

　　Basic Qualifications

　　• Ph.D. degree in Statistics, Computer Science, Applied Math, Operations Research, or a related field with publications in refereed academic journals

　　• 7+ years of hands-on experience in solving difficult machine learning problems

　　• Expert at more than one major programming languages (C++, Java, or similar) and at least one scripting language (Perl, Python, or similar)

　　• Demonstrated ability to serve as a technical lead

　　• Excellent writing skills for presenting business cases and scientific models with rigorous analyses that support results/conclusions to influence important decisions.

　　• Strong fundamentals in problem solving, algorithm design and complexity analysis

　　• Proven track in leading, mentoring, and growing teams of scientists

　　Preferred Qualifications

　　• Deep technical knowledge of machine learning and statistical methodologies

　　• Experience with deep learning toolkits and frameworks

　　• Solid software development experience

　　• Algorithm and model development experience for large-scale applications

　　• Experience with defining research and development practices in an applied environment

　　Excellent communication skills, both written and oral, with technical and business people.

　　• Professional traits, that are not unique to this position but are necessary for Amazon leaders, including exhibiting excellent judgment; maintaining relentlessly high standards; thinking strategically while staying on top of tactical execution; expecting innovation from collaborators; thinking big; having convictions; being results oriented; and inspiring passion in others about learning, research, and implementation

　　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.

　　Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $159,100/year in our lowest geographic market up to $309,400/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. Applicants should apply via our internal or external career site.