Sr. Applied Scientist, WWGS Real Estate & Store Development

About the team

We are a team of scientists passionate about leveraging data and advanced analytics to drive strategic decisions for Amazon's grocery business. Our work directly impacts Amazon's worldwide grocery store growth and development strategy. We foster a collaborative environment where team members are encouraged to think creatively, challenge assumptions, and pursue novel approaches to solving complex problems. Our team is at the forefront of applying a multitude of techniques - including GenAI - to improve our scientific solutions and products.

Key job 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.

Basic Qualifications

• 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 Qualifications

• 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