Sr. Applied Scientist Pricing Optimization, LEO Global Pricing Strategy

Description

Leo is Amazon’s low Earth orbit satellite broadband network. Its mission is to deliver fast, reliable internet to customers and communities around the world, and we’ve designed the system with the capacity, flexibility, and performance to serve a wide range of customers, from individual households to schools, hospitals, businesses, government agencies, and other organizations operating in locations without reliable connectivity.

The Sr. Applied Scientist Pricing Optimization, Leo Global Pricing Strategy will have an outsized impact on the profitability of Amazon Leo directly through building the initial foundational models to enable the business to optimize our pricing and product feature strategies. You will be building a true "0 to 1" function, powering the science behind pricing decisions and driving science automation at a global scale.

Export Control Requirement:
Due to applicable export control laws and regulations, candidates must be a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum.


A day in the life
You will design, develop, and deploy advanced machine‑learning models to predict customer‑level behavior (revenue, churn, usage, migration, product choice) and response to pricing changes. You will build robust models that capture the complexities of multi‑product bundling interactions in a subscription business model and regional nuances in supply/demand and consumer choice alternative choices. You will implement scalable inference systems, will monitor model performance, and will automate retraining. Collaboration with cross‑functional teams will be critical to ensure that technical solutions will align with business objectives and actionable strategies. Establishing 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 will be critical.

Basic Qualifications

- 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
- Experience with neural deep learning methods and machine learning

Preferred 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.
- Experience with large scale machine learning systems such as profiling and debugging and understanding of system performance and scalability

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, 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.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.