Job Description
DESCRIPTION
Amazon is looking for an Applied Scientist to help build next generation selection/assortment systems. On the Specialized Selection team within the Supply Chain Optimization Technologies (SCOT) organization, we own the selection to determine which products Amazon offers in our fastest delivery programs. We build tools and systems that enable our partners and business owners to scale themselves by leveraging our problem domain expertise, focusing instead on introspecting our outputs and iteratively helping us improve our ML models rather than hand-managing their assortment. We partner closely with our business stakeholders as we work to develop state-of-the-art, scalable, automated selection management systems.
As an Applied Scientist, you will work with software engineers, product managers, and business teams to understand the business problems and requirements, distill that understanding to crisply define the problem, and design and develop innovative solutions to address them. Our team is highly cross-functional and employs a wide array of scientific tools and techniques to solve key challenges, including supervised and unsupervised machine learning, non-convex optimization, causal inference, natural language processing, linear programming, reinforcement learning, and other forecast algorithms. Some critical research areas in our space include modeling substitutability between similar products, incorporating basket awareness and complementarity-aware logic, measuring speed sensitivity of products, modeling network capacity constraints, and supply and demand forecasting.
Key job responsibilities
You will be an end-to-end owner for the projects you support. Responsibilities include:
- Understanding business requirements and existing challenges and map them to the right scientific solution;
- Designing effective, scalable, and achievable solutions to key business problems;
- Developing the right set of metrics to evaluate efficacy of your models and solutions;
- Prototyping and analyzing new models and business logic;
- Productionizing your scientific solutions, including writing production-quality critical path code;
- Communicating, both written and verbally, with both technical and business audiences throughout each project;
- Publishing findings in internal and/or external conferences and interfacing with the scientific community;
- Mentoring and developing the scientist community across the organization
To help describe some of our challenges, we created a short video about SCOT at Amazon:
BASIC QUALIFICATIONS
- Master's degree in computer science, mathematics, statistics, machine learning or equivalent quantitative field
- Experience programming in Java, C++, Python or related language
- Experience with SQL and an RDBMS (e.g., Oracle) or Data Warehouse
Job Tags
Full time,