Applied Scientist, WWGS Real Estate & Store Development

- PhD, or Master's degree and 5+ years of building machine learning models or developing algorithms for business application experience
- Experience programming in Java, C++, Python or related language
- Experience in solving business problems through machine learning, data mining and statistical algorithms
- Experience in investigating, designing, prototyping, and delivering new and innovative system solutions
- Currently has, or is in the process of obtaining, a PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field
- Experience applying theoretical models in an applied environment
- Experience in professional software development
- Have publications at top-tier peer-reviewed conferences or journals

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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.

USA, WA, Seattle - 142,800.00 - 193,200.00 USD annually
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 an Applied Scientist to join us in developing advanced forecasting models, optimization models, and analytical tools to support critical real estate and store planning decisions for Amazon's Worldwide Grocery business, including Whole Foods Market.

Our team is responsible for developing predictive models and tools to support Real Estate and Topology analysts in making important decisions regarding our stores—including new store openings, relocations, closures, remodels, design, new formats, and more. We leverage statistical modeling, machine learning, and GenAI to build solutions for store sales forecasting, sales transfer effects, macrospace optimization, store network optimization, store network diffusion planning, and causal effects.

As an Applied Scientist on our team, you will apply your technical and analytical skills to tackle complex business problems and develop innovative solutions to improve our forecasting and decision-making capabilities. You will collaborate with a diverse team of scientists, economists, and business partners to identify opportunities, develop hypotheses, build internal products, and translate analytical insights into actionable recommendations for Executive Leadership.

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 end-to-end solutions, tools and frameworks to scale our ML model development 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.
- Stay current on latest developments in relevant fields and propose innovative approaches.

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.