Description Amazon Web Services (AWS) offers a broad set of global compute, storage, database, analytics, application, and deployment services that help organizations move faster, lower IT costs, and scale applications. These services are trusted by the largest enterprises and the hottest start-ups to power a wide variety of workloads including web and mobile applications, data processing and warehousing, storage, archive, and many others. We are looking for an applied scientist to help us define and build a new enterprise application. AWS Applications is building services in Supply Chain Management and is looking for a scientist to tackle complex science problems in Supply Chain including demand planning, supply planning and sustainability which will be used by our customers across a wide range of industries. We operate a fast growing business and our journey has only started. Our mission is to build the most efficient and optimal supply chain software on the planet, using our science and technology as our biggest advantage. We aim to leverage cutting edge technologies in optimization, operations research, and machine learning to grow our businesses. As an Applied Scientist, you’ll design, model, develop and implement state-of-the-art models and solutions used by users worldwide. As part of your role you will regularly interact with software engineering teams and business leadership. The focus of this role is to research, develop, and deploy models to improve state-of-the-art for time series. You will have the opportunity to work on our assistant solution allowing our users to ask data questions in natural language and get intelligent insights and exceptions. Key job responsibilities Lead and partner with the engineering to drive modeling and technical design for complex business problems. Develop accurate and scalable machine learning models to solve our hardest supply chain problems. Lead complex modeling analyses to aid management in making key business decisions and set product direction. A day in the life Diverse Experiences AWS 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. Basic Qualifications - PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience - 1+ years of programming in Java, C++, Python or related language experience - Experience in patents or publications at top-tier peer-reviewed conferences or journals - Experience with neural deep learning methods and machine learning Preferred Qualifications - Experience in professional software development - - Time Series forecasting experience using statistical, machine learning and deep learning techniques. - - Have experience in large language models. 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 $136,000/year in our lowest geographic market up to $222,200/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.