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Applied Scientist, Marketplace Science

Amazon

Amazon

Santa Clara, CA, USA · United States · Santa Clara, CA, USA
Posted on Jul 18, 2024

DESCRIPTION

Amazon’s Middle Mile Planning Research and Optimization Science (mmPROS) group is looking for an Applied Scientist specializing in machine learning and optimization algorithms applicable to large-scale transportation planning and pricing problems. This includes the development of novel machine learning, reinforcement learning and causal inference techniques for better marketplace optimization solutions.

Middle Mile Air and Ground transportation represents one of the fastest growing logistics areas within Amazon. Amazon Fulfillment Services transports millions of packages via air and ground and continues to grow year over year. The scale of this operation challenges Amazon to design, build and operate robust transportation networks to minimize the overall operational cost while meeting all customer deadlines. The mmPROS group is charged with developing an evolving suite of decision support and optimization tools to facilitate the design of efficient air and ground transport networks, optimize the flow of packages within the network to efficiently align network capacity and shipment demand, set prices, and effectively utilize scarce resources, such as aircraft and trucks. Time horizons for these tools vary from years and months for long-term planning to hours and minutes for near-term operational decision making and disruption recovery. These tools rely heavily on mathematical optimization, stochastic simulation, meta-heuristic and machine learning techniques. In addition, Amazon often finds existing techniques not effectively matching our unique business needs, which necessitates the innovation and development of new approaches and algorithms for an adequate solution.

As an Applied Scientist supporting middle mile transportation, you will be working closely with different teams including business leaders and engineers to design and build scalable products operating across multiple transportation modes. You will create experiments and prototype implementations of new learning algorithms and prediction techniques. You will have exposure to top level leadership to present findings of your research. You will also work closely with other scientists and also engineers to implement your models within our production system. You will implement solutions that are exemplary in terms of algorithm design, clarity, model structure, efficiency, and extensibility, and make decisions that affect the way we build and integrate algorithms across our product portfolio.

Key job responsibilities
Use statistical and machine learning models to solve ambiguous transportation problems.
Write production-level code to deliver the models.
Support model performance monitoring, experimentation and propose enhancements accordingly.

About the team
The Amazon Freight team under mmPROS is responsible for the cost prediction, pricing and demand forecast related to Amazon's shipper-facing freight business. Amazon carries Truckload (TL), Less-Than-Truckload (LTL) and Intermodal (IM) shipments for external shippers using capacity from Amazon’s Middle Mile transportation network.

BASIC QUALIFICATIONS

- PhD, or Master's degree and 2+ years of CS, CE, ML or related field experience
- 2+ years of programming in Java, C++, Python or related language experience
- Experience building machine learning models or developing algorithms for business application
- Strong problem-solving ability and the ability to work in ambiguous and constantly evolving environment.

PREFERRED QUALIFICATIONS

- Hands-on experiences with predictive modeling, long-term value modeling and price optimization techniques.

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.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136,000/year in our lowest geographic market up to $222,200/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 https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.