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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 a Research 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. Basic Qualifications: - PhD, or Master's degree and 4+ years of quantitative field research experience
- Experience investigating the feasibility of applying scientific principles and concepts to business problems and products
- Experience analyzing both experimental and observational data sets Preferred Qualifications: - Knowledge of R, MATLAB, Python or similar scripting language
- Experience with agile development
- Experience building web based dashboards using common frameworks
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.
USA, WA, Seattle - 136,000.00 - 184,000.00 USD annually
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