- Seattle, WA
Amazon Web Services (AWS) provides companies of all sizes with an infrastructure services platform in the cloud ("cloud computing"). With AWS you can requisition compute power, storage, and many other services gaining access to a suite of elastic IT infrastructure services as your business demands them. AWS is the leading platform for designing and developing applications for the cloud and is growing rapidly with hundreds of thousands of companies in over 190 countries on the platform.
The Worldwide Commercial Predictive Analytics and Insights team uses machine learning, econometrics, and data science to optimize AWS's service catalogue, driving customer engagement and generate insights to guide AWS sales strategy. We use detailed customer behavioral and usage data to predict and understand what customers want from AWS.
We are looking for a customer obsessed Applied Scientist who can apply the latest research, state of the art algorithms and machine learning to build highly scalable models in support of predictive research and analytics. The ideal candidate will work closely with business leaders and to identify opportunities to drive business growth by applying machine learning and building out predictive models to support analytics and insights. We are looking for someone who can build scalable tools to not only process the data, but transform it into actionable information. In addition, the final candidate must possess excellent interpersonal skills, strong written communication skills, be highly collaborative, and provide thought leadership and guidance across the team.
Location: Strong preference for this position to be in Seattle, but open to these additional locations: Boston. Relocation offered from within the US to any of these locations.
Inclusive Team Culture
Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have twelve employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon's culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.
Our team puts a high value on work-life balance. It isn't about how many hours you spend at home or at work; it's about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.
Mentorship & Career Growth
Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we're building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.
• Ph.D./M.S. in Computer Science, Machine Learning, Operational Research, Statistics or a related quantitative field;
• 3+ years of hands-on experience in predictive modelling and analysis;
• 1+ years hands-on experience in Python, Scala, Java, C#, C++ or other similar languages;
• 1+ years professional experience in software development;
• Proficiency in model development, model validation and model implementation for large-scale applications;
• Ph.D. in Computer Science, Machine Learning, Operational Research, Statistics or a related quantitative field;
• Excellent Computer Science fundamentals in data structures, problem solving, algorithm design and complexity analysis;
• Ability to convey mathematical results to non-science ;
• Strength in clarifying and formalizing complex problems.
• Experience with defining research and development practices in an applied environment;
• Experience working with Deep Learning frameworks (MxNet, TensorFlow, etc.);
• Proven track record in technically leading and mentoring scientists;
• Superior verbal and written communication and presentation skills, ability to convey rigorous mathematical concepts and considerations to non-experts.
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.
Benefits overview: https://amazon.jobs/en/internal/landing_pages/benefitsoverview-us
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