We are looking for a talented, organized, and customer-focused technical leader to join our Product Intelligence science group, with a charter to derive deep neural product relationships, quantify substitution and complementarity effects, and publish trust-preserving probabilistic price ranges on all products listed on Amazon.
This role requires an individual with excellent scientific modeling and system design skills, outstanding business acumen, and an entrepreneurial spirit. We are looking for an experienced leader who is a self-starter comfortable with ambiguity, demonstrates strong attention to detail, and has the ability to work in a fast-paced and ever-changing environment.
Key job responsibilities
- Develop the team. Mentor a highly talented group of applied machine learning scientists & researchers.
- See the big picture. Shape long term vision for Amazon's science-based competitive, perception-preserving pricing techniques
- Build strong collaborations. Partner with product, engineering, and science teams within Pricing & Promotions to deploy machine learning price estimation and error correction solutions at Amazon scale
- Stay informed. Establish mechanisms to stay up to date on latest scientific advancements in machine learning, neural networks, natural language processing, probabilistic forecasting, and multi-objective optimization techniques. Identify opportunities to apply them to relevant Pricing & Promotions business problems
- Keep innovating for our customers. Foster an environment that promotes rapid experimentation, continuous learning, and incremental value delivery.
- Deliver Impact. Develop, Deploy, and Scale Amazon's next generation foundational price estimation and understanding system
About the team
Within Pricing & Promotions Science, the Product Intelligence team leverages planet scale multi-modal data on billions of Amazon and external competitor products to build advanced machine learning models for product similarity, substitutability, error detection & correction, and probabilistic price estimation. We preserve long term customer trust by ensuring Amazon's prices are always competitive and error free
BASIC QUALIFICATIONS
- Ph.D. or Master's degree in Computer Science, Statistics, Machine Learning, Natural Language Processing, Financial Modeling, or related field.
- 10+ years of broad AI/ML research experience on large-scale industry problems in pricing, time series, forecasting, trading, recommendation, or natural language domains
- 5+ years of experience technical leadership of applied science teams
- 5+ years of experience with AWS or Amazon ML tech stack and tooling
- Expertise in deep learning methods
- A track record of balancing project delivery with longer term research, demonstrated via publications, or contributions to the open source community.
- Proficiency in programming languages such as Python and frameworks like TensorFlow, PyTorch
- Proven written and verbal technical communication with the ability to present complex topics clearly to audiences with varying levels of technical familiarity
PREFERRED QUALIFICATIONS
- Experience delivering and scaling AI/ML based solutions involving Probabilistic Forecasting, LLMs, Active Learning, Human Annotation
- Experience of influencing business or company strategy through cutting edge research and long term science vision
- Experience partnering with academic institutions for collaborations and talent acquisition
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.
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.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $179,000/year in our lowest geographic market up to $309,400/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.