Do you want to be part of an innovative and rapidly growing business? Are you looking for a role with ownership and the ability to work across global teams to launch a product?
AWS’s Worldwide Revenue Operations Segmentation and Planning (WWRO S&P) team provides the technology, tools, and processes to support the rapidly growing world-wide AWS Sales organization. This includes finding inventive ways to scale the business, which will be critical for AWS to continue its incredible growth.
The WWRO S&P team is looking for an Applied Scientist to play a significant part in leading machine learning programs that enable our global Sales to go to market. Sample initiatives could include the improvement of how we classify customers, make territory recommendations, forecast revenue, and more. This Applied Scientist will work hand in hand with product managers to identify opportunities to provide intelligence and prediction to planning, goal tracking, segmentation, and resourcing to drive better decision making.
The Applied Scientist will need to dive deep with the development team to design, train, test, and deploy machine learning models. You will contribute to innovative features, improve our services based on customer requirements and help maintain a highly scalable data and model management infrastructure that supports cutting-edge research. You will be responsible for translating business and engineering requirements into deliverables and software products. This role requires an individual with excellent quantitative modeling skills and the ability to apply statistical/machine learning, econometric, and coding skills.
The successful candidate will have a strong technical background, be highly collaborative, globally minded and have a high level of customer focus. You should be a motivated self-starter that works well with others in a dynamic, ambiguous environment. You should have excellent business, technical, and communication skills to be able to work across countries and markets, dev teams, and with business owners to define and deliver improvements.
Location: Position may be based in Seattle, WA; Boston, MA; Arlington, VA; or Dallas, TX. Amazon will provide relocation assistance from within the US only to these locations.
Applied Scientist Responsibilities
· Use machine learning and analytical techniques to create scalable solutions for business problems
· Analyze and extract relevant information from large amounts of historical business data to help automate and optimize key processes
· Design, development and evaluation of highly innovative models for predictive learning
· Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation
· Research and implement novel machine learning and statistical approaches
· Work closely with data & software engineering teams to build model implementations and integrate successful models and algorithms in production systems at very large scale
Position may be based in Seattle, WA; Boston, MA; Arlington, VA; or Dallas, TX
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. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded professional and enable them to take on more complex tasks in the future.
· Ph.D./M.S. in Computer Science, Machine Learning, Operational Research, Statistics, Mathematics or a related quantitative field
· 3+ years of hands-on experience in predictive modelling and analysis
· 2+ years hands-on experience in Python, Scala, Java, C#, C++ or other similar languages
· 1+ years professional experience in software development
· Experience 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
· Experience with AWS services like SageMaker, Amazon Forecast, S3, Glue ETL, or similar tools is a plus, but not required
· Excellent Computer Science fundamentals in data structures, problem solving, algorithm design and complexity analysis
· Ability to convey mathematical results to non-science
· Experience working with product management in an agile development environment
· 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.