Amazon
Applied Scientist, Pricing and Promotion Optimization
Amazon, Seattle, Washington, us, 98127
Applied Scientist, Pricing and Promotion Optimization Job ID: 2679643 | Amazon.com Services LLCAmazon's Pricing & Promotions Science is seeking a driven Applied Scientist to harness planet scale multi-modal datasets and navigate a continuously evolving competitor landscape to regularly generate fresh customer-relevant prices on billions of Amazon and Third Party Seller products worldwide.
Please read the following job description thoroughly to ensure you are the right fit for this role before applying.
We are looking for a talented, organized, and customer-focused applied researcher to join our Pricing and Promotions Optimization science group, with a charter to measure, refine, and launch customer-obsessed improvements to our algorithmic pricing and promotion models across all products listed on Amazon.
This role requires an individual with exceptional machine learning and reinforcement learning modeling expertise, excellent cross-functional collaboration skills, outstanding business acumen, and an entrepreneurial spirit. We are looking for an experienced innovator 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
See the big picture. Understand and influence the 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.Successfully execute & deliver. Apply your exceptional technical machine learning expertise to incrementally move the needle on some of our hardest pricing problems.About the team The Pricing Discovery and Optimization team within P2 Science owns price quality, discovery and discount optimization initiatives, including criteria for internal price matching, price discovery into search, p13N and SP, pricing bandits, and Promotion type optimization. We leverage planet scale data on billions of Amazon and external competitor products to build advanced optimization models for pricing, elasticity estimation, product substitutability, and optimization. We preserve long term customer trust by ensuring Amazon's prices are always competitive and error free.BASIC QUALIFICATIONS
PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience.Experience programming in Java, C++, Python or related language.Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing.2+ years of hands-on predictive modeling and large data analysis experience.PREFERRED QUALIFICATIONS
Experience building machine learning models or developing algorithms for business application.Experience in patents or publications at top-tier peer-reviewed conferences or journals.Reinforcement Learning and Optimization 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.
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Please read the following job description thoroughly to ensure you are the right fit for this role before applying.
We are looking for a talented, organized, and customer-focused applied researcher to join our Pricing and Promotions Optimization science group, with a charter to measure, refine, and launch customer-obsessed improvements to our algorithmic pricing and promotion models across all products listed on Amazon.
This role requires an individual with exceptional machine learning and reinforcement learning modeling expertise, excellent cross-functional collaboration skills, outstanding business acumen, and an entrepreneurial spirit. We are looking for an experienced innovator 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
See the big picture. Understand and influence the 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.Successfully execute & deliver. Apply your exceptional technical machine learning expertise to incrementally move the needle on some of our hardest pricing problems.About the team The Pricing Discovery and Optimization team within P2 Science owns price quality, discovery and discount optimization initiatives, including criteria for internal price matching, price discovery into search, p13N and SP, pricing bandits, and Promotion type optimization. We leverage planet scale data on billions of Amazon and external competitor products to build advanced optimization models for pricing, elasticity estimation, product substitutability, and optimization. We preserve long term customer trust by ensuring Amazon's prices are always competitive and error free.BASIC QUALIFICATIONS
PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience.Experience programming in Java, C++, Python or related language.Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing.2+ years of hands-on predictive modeling and large data analysis experience.PREFERRED QUALIFICATIONS
Experience building machine learning models or developing algorithms for business application.Experience in patents or publications at top-tier peer-reviewed conferences or journals.Reinforcement Learning and Optimization 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.
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