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Senior Applied Scientist, Specialized Selection

Job ID: 1888986 | Services LLC


Job summary
Amazon is looking for an outstanding Senior 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 a Senior 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.

You will be a science tech leader for the team. As a Senior Applied Scientist you will:

• Lead a team of scientists to innovate on state-of-the-art assortment planning systems for limited-shelf businesses.
• Set the scientific strategic vision for the team. You lead the decomposition of problems and development of roadmaps to execute on it.
• Set an example for other scientists with exemplary scientific analyses; maintainable, extensible, and well-tested code; and simple, intuitive, and effective solutions.
• Influence team business and engineering strategies.
• Exercise sound judgment to prioritize between short-term vs. long-term and business vs. technology needs.
• Communicate clearly and effectively with stakeholders to drive alignment and build consensus on key initiatives.
• Foster collaborations between scientists across Amazon researching similar or related problems.
• Actively engage in the development of others, both within and outside the team.
• Engage with the broader scientific community through presentations, publications, and patents.

To help describe some of our challenges, we created a short video about SCOT at Amazon:

Key job responsibilities
"Machine Learning", optimization, ML, python, NLP, "reinforcement learning", "causal inference", "supervised learning", "unsupervised learning", "assortment planning", "recommendation systems", "experimental design", "Natural Language Processing"


· 5+ years industry experience in science and/or software engineering;
· PhD in computer science, operations research, applied mathematics or a related field;
· Broad knowledge of machine learning and optimization;
· Experience designing, prototyping, and productionizing large-scale scientific models;
· Expert knowledge in at least one of following fields: Machine Learning (Supervised and/or Unsupervised, Non-Convex Optimization, Linear Programming, Natural Language Processing, Reinforcement Learning, Causal Inference, Forecasting
· Fluency in a high-level modeling language such as Python;
· Sound working knowledge of software engineering fundamentals, including logical and maintainable code, data structures and algorithms, and object oriented design;
· Strong communication skills, both written and verbal;
· Ability to navigate conflicting priorities and ambiguous problem space(s);
· Ability to convey rigorous mathematical concepts and considerations to business and product teams


· Familiarity/experience with retail industry and the assortment planning space
· Proficiency in at least one programming language such as Java, Scala, or C++

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