Amazon Web Services (AWS) is the leading provider of cloud computing services in the world, offering a broad range of highly reliable, scalable, low-cost cloud services across over 190 countries. AWS infrastructure powers hundreds of thousands of enterprise, government and start-up businesses.
AWS Central Economics is an interdisciplinary science team that operates at the cutting edge of economics, statistical analysis, and machine learning. The team sits at the center of AWS and advises senior leadership. Our mission is to solve problems that have high risk and abnormally high returns. We leverage the strengths of our scientists to build solutions for some of the toughest business problems here at Amazon AWS.
We are looking for an Applied Scientist to explore and develop both supervised and unsupervised models from large an complex datasets. You will develop and applying machine learning methods both for prediction, classification, and to answer cause-and-effect questions. The ideal candidate will have hands-on experience and be able to make the right decisions about technology, models, and methodology. You will strive for simplicity, and demonstrate significant creativity and high judgment backed by statistical proof. Working collaboratively, you will develop solutions to complex problems, such as designing scalable algorithms to classify workloads run on AWS; attribute revenue across 200+ AWS services; analyze how customers discover, test, adopt, and onboard AWS services to save costs, maximize efficiency, accelerate development, and scale. The output of your algorithms will inform leadership-level decisions and feed into automated systems that enable multiple orgs within AWS to serve our customers faster and better.
This is a role that combines science leadership, organizational ability, technical strength, product focus and business understanding. The ideal candidate will be an independent thinker who can make convincing, information-based arguments. With a focus on delivering high quality results, this individual will be able to work equally well with Science, Economics and business teams. This person will have sound judgment and help recruit and groom high caliber science talent. This role is tailor-made for you if you are passionate about solving problems at the intersection of Machine learning and Causal Inference.
As an Applied Scientist, you will continue to contribute to the research community, by working with other scientists across Amazon, AWS, our partners, and our network, as well as collaborating with academic researchers and publishing papers, in addition to solving the networking challenges we have within AWS. Our Science community values teamwork, supports continued learning, and recognizes the need to take risks and try new ideas that may fail.
As an Applied Scientist in AWS Central Economics you will:
· Drive applied science projects in machine learning end-to-end: from ideation, through testing and prototyping, to launch.
· Propose viable ideas to advance models and algorithms, with supporting argument, experiment, and eventually preliminary results.
· Invent ways to overcome technical limitations and enable new forms of analyses to drive key technical and business decisions.
· Collaborate with economists, scientists, product managers, engineers, and stockholders to design and implement software solutions for science problems.
· Present results, reports, and data insights to both technical and business leadership.
· Constructively critique peer research and mentor junior scientists.
· Innovate and contribute to Amazon’s science community and external research communities.
· PhD degree in Computer Science, Machine Learning, Operational Research, Statistics or a related quantitative field with 4+ years of applied research experience or a Master's degree and 6+ years of experience of applied research experience
· 3+ years of experience in building machine learning models for business applications
· Experience programming in Java, C++, Python, R or related language
· 4+ years of hands-on experience applying theoretical models in an applied environment
· Experience with AWS technologies
· Significant peer reviewed scientific contributions in premier journals and conferences
· Strength in clarifying and formalizing complex problems.
· Experience with defining research and development practices in an applied environment
· Superior verbal and written communication and presentation skills, ability to convey rigorous mathematical concepts and considerations to non-science stakeholder.
· Proven track record in technically leading and mentoring scientists and/or software engineers
· Familiarity with problems and algorithms at the intersection of Machine Learning and Causal Inference
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.