Overview
If you have ever bought or sold anything on Amazon, you have touched Amazon Marketplace. Amazon’s Marketplace business is one of the largest in the world. We are now in 23 countries and growing fast, with customers in many more. Amazon’s platform powers Amazon’s Marketplace businesses, and sellers rely on this platform and our support to start selling and grow their business. Amazon Marketplace enables millions of sellers worldwide to list hundreds of millions of products and manage orders across dozens of categories and languages. While working with millions of sellers worldwide, we constantly strive to improve the selection for customers and the capabilities of our platform for sellers.
The Seller Fulfillment Services (SFS) team is looking for a motivated and innovative Applied Scientist with strong analytical skills and practical experience to join our science team. As a key member of the SFS science team, you will provide expertise that helps accelerate the business. You will build science solutions that provide our customers with the largest selection of merchants at the lowest costs and the most reliable delivery service, regardless of the seller. You will research, design, and improve models that impact Amazon’s customers directly. You will work in a highly collaborative environment, partnering with science, product management, engineering, operations, finance, business intelligence and analytics teams to develop models to solve business problems.
You will need to understand business requirements and translate them into complex analytical outputs. You will design tests to explain performance of the models from the perspective of customer impact and cost. You will create machine‑learning models that capture features impacting performance. You should be comfortable building prototypes, testing, and improving them based on real‑time data feedback. You should be able to present your model and findings to a wide range of stakeholders.
An ideal candidate will be an expert in machine learning, operations research, and statistics, applying theoretical models in an applied environment and relying on the latest advances in machine learning, optimization, stochastic modeling, and engineering. The candidate will work on feature engineering, modeling, probabilistic modeling, hyper‑parameter tuning, scalable inference methods and latent variable models. Challenges will involve dealing with very large data sets and throughput requirements.
Key Job Responsibilities
* Design, implement, test, deploy, and maintain innovative science solutions to accelerate our business.
* Create experiments and prototype implementations of new learning algorithms and prediction techniques.
* Collaborate with scientists, engineers, product managers, and stakeholders to design and implement software solutions for science problems.
* Use best practices to ensure a high standard of quality for all team deliverables.
Basic Qualifications
* Master's degree in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field.
* 3+ years of building machine‑learning models or developing algorithms for business application experience.
* 3+ years of solving business problems through machine learning, data mining and statistical algorithms experience.
* Experience in algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high‑performance computing.
* Experience in patents or publications at top‑tier peer‑reviewed conferences or journals.
* Experience programming in Java, C++, Python or related language.
* Experience in professional software development.
* Experience implementing algorithms using toolkits and self‑developed code.
Preferred Qualifications
* PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field.
* 5+ years of building machine‑learning models or developing algorithms for business application experience.
* Knowledge of architectural concepts and algorithms, schedule trade‑offs and new opportunities with technical team members.
Inclusive Culture
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 https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
Amazon is an equal‑opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
#J-18808-Ljbffr