Applied Scientist II, Partner Growth Experience

Amazon; Seattle (WA); On-site; USD 100,000 - 150,000; Full time

Job summary

An established industry player is seeking an Applied Scientist to innovate machine learning solutions for their Consumer Electronics business. This role involves developing advanced models that enhance decision-making and automate processes within the Smart Retail project. You will collaborate with cross-functional teams to identify impactful opportunities, ensuring seamless integration and measurable results. Ideal candidates will have a strong background in machine learning, programming, and experience with large-scale systems. Join a culture that values inclusivity and empowers you to achieve the best outcomes for customers.

Qualifications

• PhD or Master's degree with 3+ years of experience in CS, CE, ML.
• Experience building models for business applications.

Responsibilities

• Design and deploy advanced machine learning models at scale.
• Partner with teams to deliver science-driven solutions.

Skills

Machine Learning

Java

C++

Python

Data Mining

Algorithms and Data Structures

Education

PhD in Computer Science

Master's degree in Computer Science

Tools

Spark

Sagemaker

Job description

Applied Scientist II, Partner Growth Experience

EU INTech Partner Growth Experience(PGX) is seeking an Applied Scientist to lead the development of machine learning solutions for the EU Consumer Electronics business. In this role, you will push the boundaries of advanced ML techniques and collaborate closely with product and engineering teams to create innovative buying and forecasting solutions for the business.
These new models will primarily benefit Smart Retail project that aims to revolutionize CPFR (Collaborative Planning, Forecasting, and Replenishment) Retail operations, driving automation, enhancing decision-making processes, and achieving scale across eligible categories such as PC, Home Entertainment or Wireless. Smart Retail solution is composed of an internal interface automating selection management mechanisms currently performed manually, followed by the creation of a vendor-facing interface on Vendor Central reducing time spent collecting required inputs. The project's key functionalities include (i) a Ranging model operating from category to product attributes level, pre-ASIN creation and when selection is substitutable, (ii) an advanced forecasting model designed for new selection and accounting cannibalization, (iii) ordering inputs optimization in line with for SCOT guideline compliance, and intelligent inventory management for sell-through tracking. Smart Retail success also depends on its integration with existing systems (SCOT) to minimize manual intervention and increase accuracy.

Key job responsibilities
* Design, develop, and deploy advanced machine learning models to address complex, real-world challenges at scale.
* Build new forecasting and time-series models or enhance existing methods using scalable techniques.
* Partner with cross-functional teams, including product managers and engineers, to identify impactful opportunities and deliver science-driven solutions.
* Develop and optimize scalable ML solutions, ensuring seamless production integration and measurable impact on business metrics.
* Continuously enhance model performance through retraining, parameter tuning, and architecture improvements using Amazon’s extensive data resources.
* Lead initiatives, mentor junior scientists and engineers, and promote the adoption of ML methodologies across teams.
* Stay abreast of advancements in ML research, contribute to top-tier publications, and actively engage with the scientific community.

BASIC QUALIFICATIONS

- PhD, or Master's degree and 3+ years of CS, CE, ML or related field experience
- 3+ years of building models for business application 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

PREFERRED QUALIFICATIONS

- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- 3+ years of hands-on predictive modeling and large data analysis experience
- Experience working with large-scale distributed systems such as Spark, Sagemaker or similar frameworks

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.

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