DESCRIPTION:
mmPROS Surface Research Science seeks an exceptional Applied Scientist with expertise in forecasting and risk modeling to optimize Amazon's middle mile transportation network, the backbone of its logistics operations. Amazon's middle mile transportation network utilizes a fleet of semi-trucks, trains, and air planes to transport millions of packages per day as well as other freight between warehouses, vendor facilities, and customers, on time and at low cost. <br><br>The mmPROS Surface Research Science team delivers innovation, models, algorithms, and other scientific solutions to efficiently plan and operate the middle mile surface (truck and rail) transportation network. The team focuses on large-scale problems in vehicle route planning, capacity procurement, network design, forecasting, and equipment re-balancing. Your role will be to build innovative forecasting, risk quantification, and other machine learning models to decide the optimal long-term and short-term strategy for truck capacity procurement and other planning problems.<br><br>Your models will impact business decisions worth billions of dollars and improve the delivery experience for millions of customers. You will operate as part of a team of innovative, experienced scientists working on machine learning and optimization problems, and you will work in close collaboration with partners across product, engineering, business intelligence, and operations. <br><br>Key job responsibilities<br>- Design, develop, and implement forecasting models, risk models, and other machine learning models to inform our hardest planning decisions.<br>- Implement machine learning and risk models in Amazon's production software.<br>- Lead and partner with product, engineering, and operations teams to drive modeling and technical design for complex business problems.<br>- Lead complex modeling and data analyses to aid management in making key business decisions and set new policies.<br>- Write documentation for scientific and business audiences.<br><br>About the team<br>This role is part of mmPROS Surface Research Science. Our mission is to build the most efficient and optimal transportation network on the planet, using our science and technology as our biggest advantage. We aim to leverage cutting edge technologies in optimization, operations research, and machine learning to grow our businesses and solve Amazon's unique logistical challenges.<br><br>Scientists in the team work in close collaboration with each other and with partners across product, software engineering, business intelligence, and operations. They regularly interact with software engineering teams and business leadership.
BASIC QUALIFICATIONS:
- 3+ years of building machine learning models or developing algorithms for business application experience<br>- PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field, or Master's degree and 10+ years of industry or academic research experience<br>- Knowledge of programming languages such as C/C++, Python, Java or Perl<br>- Experience with neural deep learning methods and machine learning
PREFERRED QUALIFICATIONS:
- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.<br>- Experience with large scale distributed systems such as Hadoop, Spark etc.<br><br>Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.<br><br>Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.<br><br>Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit <a href="https://amazon.jobs/content/en/how-we-hire/accommodations">https://amazon.jobs/content/en/how-we-hire/accommodations</a> for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.<br><br>Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit <a href="https://www.aboutamazon.com/workplace/employee-benefits">https://www.aboutamazon.com/workplace/employee-benefits</a>. This position will remain posted until filled. Applicants should apply via our internal or external career site.