Sr. Applied Scientist, Pricing and Promotion Optimization

DescriptionAmazons Price Optimization science team is seeking a Senior Scientist to harness planet scale multi-modal datasets, navigate a continuously evolving competitor landscape, in order to regularly generate fresh customer-relevant prices on billions of Amazon and Third Party Seller products worldwide. This is a high visibility, high impact role for a seasoned, intellectually curious scientist able to partition customer problems into discrete solvable components, build or leverage existing approaches to deliver those components, and innovate to deploy the science into measurable customer-improving outputs.This role requires an individual with exceptional machine learning and reinforcement learning modeling expertise, a strong statistical background, 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.Price is a highly relevant input into many partner-team architectures, and is highly relevant to the customer, therefore this role creates the opportunity to drive extremely large impact (measured in Bs not Ms), but demands careful thought and clear communication.Key job responsibilitiesWe are hiring a senior applied scientist to drive our pricing optimization initiatives. The Price Optimization science team drives cross-domain and cross-system improvements through:* Using cross-ASIN signals to optimally price bundles, ensure price rationality across products, and discovering and launch optimal promotional bundles* invent and deliver price optimization, simulation, and competitiveness tools for 3p Sellers.* shape and extend our bandit optimization platform - a pricing centric multi-armed bandit platform that automates the optimization of various system parameters and price inputs.* Promotion optimization initiatives exploring CX, discount amount, and cross-product optimization opportunities.* Identifying opportunities to optimally price across systems and contexts (marketplaces, request types, event periods)About the teamThe Pricing Optimization science team owns price quality, discovery and discount optimization initiatives across Amazons internal pricing architecture as well as upwards into the customer discovery funnel. 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- 4+ years of applied research experience- 3+ years of building machine learning models for business application experience- PhD, or Master's degree and 6+ years of applied research experience- Experience programming in Java, C++, Python or related language- 6+ years of building machine learning models or developing algorithms for business application experiencePreferred Qualifications- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.- Experience with large scale distributed systems such as Hadoop, Spark etc.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.Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/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.