Do you want to transform millions of customer's experience of interacting with AWS products using artificial intelligence and machine learning? Do you want to see the impacts of your work moving the needles on the billions dollars of AWS business? Do you want to stay on the cutting edge of technology (e.g. Gen AI, graph neural network, reinforcement learning, and forecasting models) to build scalable ML products that help AWS grow? The AWS Product Analytics and Data Science (PANDAS) team is at the forefront of leveraging cutting-edge AI/ML technology and infrastructure to redefine how internal product teams interact with and derive insights from their data. Our vision is to use artificial intelligence and machine learning to enable AWS product teams and business leaders to drive product growth and create personalized, optimized, and simplified product experience. We strive to improve customersâ product experience, directly influence AWSâs top line and bottom line, and help AWS business leaders drive product growth. We want to be a centralized ML platform team that democratizes ML capabilities to AWS product teams and transform their product and customer experience. You will work cross-functionally, typically collaborating with several teams of scientists, data engineer, product managers, and business leaders (GM/VP) in order to influence the business and technical strategy for a complex, high-performance organization. You will also drive impactful, long-term choices on system architecture, spearhead a high-quality science and engineering culture, leading the science innovation and business impacts across the org. Key job responsibilities - Utilize state-of-the-art machine learning, deep learning, and statistical techniques to develop models that can predict/classify business outcomes, automate decision-making processes, and enhance user experiences. - Conduct comprehensive data analyses to extract insights, identify patterns, and inform model development, utilizing large and complex datasets from diverse sources. - Design, development, and evaluation of innovative models for predictive learning, ensuring high-quality standards are maintained. Drive the best science and engineering practices. - Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation, and model implementation. - Monitor and assess the performance of deployed models, implementing continuous improvement strategies to adapt to changing data patterns and business requirements. - Work cross-functionally with data & software engineering teams to build model implementations and integrate successful models and algorithms in production systems at very large scale, focusing on scalability, efficiency, and performance. - Research and implement novel machine learning and statistical approaches that can contribute to state of the art science with publication A day in the life In your role as an applied scientist, you will play a pivotal role in shaping product development by working closely with product managers, software engineers, and designers to translate business objectives into actionable scientific projects. You will be instrumental in identifying and securing the necessary datasets in collaboration with data management teams. Your expertise will guide the selection and implementation of advanced statistical and machine learning methods, ensuring the development of robust models. These models will then be refined, tested, and deployed in production. You'll communicate your ML solution to stakeholders and product teams through effective verbal and written communication. About the team We are a team of scientists and engineers supporting AWS product leaders to make high impact decisions through sophisticated analytical frameworks, trusted data science methods, and scalable ML products. We came from diverse backgrounds from statistics, computer science, engineering, and business analytics. We specialized in the full end to end ML development process, including data ingestion, ETL, model development, and model deployment in production. We are supporting the data science needs across AWS EC2, Database & Analytics, and S3 teams using deep learning, graph neural network, forecasting, reinforcement learning, causal inference, etc. About AWS Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasnât followed a traditional path, or includes alternative experiences, donât let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the worldâs most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating â thatâs why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, itâs 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 Weâre continuously raising our performance bar as we strive to become Earthâs Best Employer. Thatâs why youâll 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 we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, thereâs nothing we canât achieve in the cloud. This team is part of AWS Utility Computing: Utility Computing (UC) AWS Utility Computing (UC) provides product innovations â from foundational services such as Amazonâs Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWSâs services and features apart in the industry. As a member of the UC organization, youâll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services.
