About the job
Do you want to help shape the future of Amazon's physical retail presence? Worldwide Grocery Stores (WWGS), Location Strategy and Analytics team is looking for a Sr. Applied Scientist to join us in developing advanced forecasting models, optimization models, and analytical tools to support critical real estate and network planning decisions for Amazon's Worldwide Grocery business, including Whole Foods Market.
Responsibilities
Design and implement forecasting models and machine learning solutions to predict store performance and optimize our retail network.
Analyze large datasets to uncover insights and patterns related to store performance, customer behavior, and market dynamics.
Develop and own end-to-end solutions, tools and frameworks to scale our ML model development, MLOps, and data analysis.
Leverage GenAI models to enhance user interaction with our solutions, improve overall user experience, and build new features.
Present research findings and recommendations to scientists, business leaders, and executives.
Collaborate with cross-functional teams to drive adoption of models and insights.
Mentor junior scientists, providing technical guidance and supporting their professional growth.
Stay current on latest developments in relevant fields and propose innovative approaches.
Qualifications
Minimum
PhD, or Master's degree and 10+ years of industry or academic research experience
5+ years of building machine learning models for business application experience
Experience programming in Java, C++, Python or related language
Experience in building machine learning models for business application
Preferred
PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field
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 conducting research in a corporate setting