Applied Scientist

Job ID: 1547441 | Amazon Web Services, Inc.

DESCRIPTION

The AWS Applications team builds powerful, intuitive, and market-defining business and productivity applications to help our customers stay ahead of their changing business needs, and remove the burden of undifferentiated heavy lifting that business users go through daily. These applications leverage the power of machine learning and the large ecosystem of AWS services such as SageMaker, AWS Lambda, Amazon S3, and Amazon QuickSight to provide a truly frustration-free, easy-to-use, extensible, and natural customer experience. We are hiring for a new data science team in AWS Applications to focus on solving problems at massive scale. This is a unique green-field chance to join a new team, and has tremendous opportunity for career growth.

Joining the AWS Apps team gives you the opportunity to:
· Solve challenging problems and help customers modernize their core IT applications
· Work for a company that’s a recognized leader in the cloud computing space
· Have direct impact on hundreds of thousands of users of AWS Apps services
· Be involved in the fast growing big data space – learn from the experts

What you will do here
We are looking for a seasoned applied scientist with expertise in mathematical optimization to join the team. In this position, you will play a pivotal role in building the brain behind AWS applications. You will be responsible for building models, prototypes, simulations, and state-of-the-art optimization algorithms that can scale across several product lines. You will advise and closely collaborate with product and engineering teams to develop innovative products that disrupt established industries. In this role, you will also work closely with the renowned machine learning and optimization community at Amazon.

The successful candidate must have exceptional analytical skills and demonstrated experience developing and implementing machine learning and optimization solutions in organizations. We are looking for a proven ability to execute both strategically and tactically, and someone who is excited to take on new, ambiguous projects that will be industry defining. As a senior science leader on the team, your specific responsibilities will include:
· Understand customer problems and define solutions for optimization challenges in new product areas
· Develop scalable mathematical models to help customers derive optimal or near-optimal solutions
· Prototype and implement new learning algorithms and prediction techniques
· Create simulations to test devised solutions
· Advise and collaborate with product and engineering teams to design and implement software solutions for machine learning and optimization problems
· Help hire and build a growing science community in the AWS Applications space

Inclusive Team Culture
Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten 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.
Work/Life Balance
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.
This position involves on-call responsibilities, typically for one week every two months. We don’t like getting paged in the middle of the night or on the weekend, so we work to ensure that our systems are fault tolerant. When we do get paged, we work together to resolve the root cause so that we don’t get paged for the same issue twice.
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.


BASIC QUALIFICATIONS

· Ph.D./M.S. in Computer Science, Machine Learning, Operational Research, Statistics or a related quantitative field
· 2+ years of hands-on modeling and mathematical optimization techniques tailored to meet real life problems through a record of achievements in industrial and/or academic environments
· Strength in distilling problem definitions, models, and constraints from complex business problems and requirements
· Ability to convey mathematical results to non-science stakeholders
· 2+ years hands-on experience in Python, Perl, Scala, Java, C#, C++ or other similar languages
· Experience working with open source optimization libraries (PuLP, OR Tools, SciPy) and/or with commercial solvers (FICO, Gurobi, CPLEX)

PREFERRED QUALIFICATIONS

· Ph.D. in Operations Research
· Proven track record of successfully applying ML-based and optimization solutions to complex problems in business, science, or engineering.
· Prior production level software development experience
· 3+ years of practical experience applying machine learning to solve complex problems in an applied environment
· Excellent written and verbal communication skills with teams, technical teams, and leadership

This role can be located in Arlington, VA, Austin, TX, Vancouver, Canada, or Seattle, Washington.

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, visit https://www.amazon.jobs/en/disability/us.