DESCRIPTION The Workforce Solutions Analytics and Tech team is looking for a senior Applied Scientist who is interested in solving challenging optimization problems in the labor scheduling and operations efficiency space. We are actively looking to hire senior scientists to lead one or more of these problem spaces. Successful candidates will have a deep knowledge of Operations Research and Machine Learning methods, experience in applying these methods to large-scale business problems, the ability to map models into production-worthy code in Python or Java, the communication skills necessary to explain complex technical approaches to a variety of stakeholders and customers, and the excitement to take iterative approaches to tackle big research challenges.
As a member of our team, you'll work on cutting-edge projects that directly impact over a million Amazon associates. This is a high-impact role with opportunities to designing and improving complex labor planning and cost optimization models. The successful candidate will be a self-starter comfortable with ambiguity, with strong attention to detail and outstanding ability in balancing technical leadership with strong business judgment to make the right decisions about model and method choices.
Successful candidates must thrive in fast-paced environments, which encourage collaborative and creative problem solving, be able to measure and estimate risks, constructively critique peer research, and align research focuses with the Amazon's strategic needs.
Key job responsibilities
• Candidates will be responsible for developing solutions to better manage and optimize flexible labor capacity. The successful candidate should have solid research experience in one or more technical areas of Operations Research or Machine Learning. As a senior scientist, you will also help coach/mentor junior scientists on the team.
• In this role, you will be a technical leader in applied science research with significant scope, impact, and high visibility. You will lead science initiatives for strategic optimization and capacity planning. They require superior logical thinkers who are able to quickly approach large ambiguous problems, turn high-level business requirements into mathematical models, identify the right solution approach, and contribute to the software development for production systems.
• Invent and design new solutions for scientifically-complex problem areas and identify opportunities for invention in existing or new business initiatives.
• Successfully deliver large or critical solutions to complex problems in the support of medium-to-large business goals.
• Apply mathematical optimization techniques and algorithms to design optimal or near optimal solution methodologies to be used for labor planning.
• Research, prototype, simulate, and experiment with these models and participate in the production level deployment in Python or Java.
We are open to hiring candidates to work out of one of the following locations:
Arlington, VA, USA | Austin, TX, USA | Bellevue, WA, USA | Nashville, TN, USA | Seattle, WA, USA | Tempe, AZ, USA BASIC QUALIFICATIONS - 3+ years of building machine learning models for business application experience
- PhD, or Master's degree and 6+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning
