Applied Scientist II, Retail Pricing Science and Research

Job summary
We are seeking experienced Applied Machine Learning Scientists to develop innovative pricing, promotions, and demand models that adapt to constantly shifting marketplace dynamics, continuing to produce optimal competitive prices for our customers, all while scaling to hundreds of millions of products globally.


Key job responsibilities

• You will develop ML models for various price optimization systems using deep learning, reinforcement learning, and optimization methods.
• You will partner with scientist, economists, engineers, and product leaders to break down complex pricing challenges, identify key requirements, innovate, design, & deploy appropriate scientific solutions, and successfully drive the creation of positive customer and business impact.
• You will summarize your research findings, and present via internal papers and science forms.
• You are adept at translating business objectives into specific quantitative approaches that can be solved with the vast amount of available Amazon data.
• You are passionate about the getting the science details right, while balancing the practical considerations of real world production models.

About the team
Retail Pricing Science and Research is a centralized machine learning team that develops models, solutions, and platforms that drive pricing for products sold by Amazon worldwide, with a dual focus on both competitiveness and long term financial optimality.

Basic Qualifications

• PhD or equivalent Master's Degree plus 4+ years of experience in CS, CE, ML or related field
• Experience programming in Java, C++, Python or related language

• Submitted Patents, and/or peer-reviewed scientific contributions in premier journals and conferences.
• Experience working with multiple data modalities, including Images, Text, and Structured datasets.

Preferred Qualifications

• Ph.D. in Computer Science, Machine Learning, Statistics or a related quantitative field.
• Experience using Reinforcement Learning, Contextual Bandits, or Probabilistic Programming in real-world applications.
• Expertise in Deep Learning and statistics (particularly Bayesian inference and causal inference) for Time Series and NLP.
• Experience with industry-standard frameworks such as PyTorch and Pyro or equivalent frameworks.
• Previous experience in pricing systems.

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.