At Amazon, we strive to be Earth's most customer-centric company. Our International Seller Growth team expands our marketplace globally, providing customers with extensive product selection while empowering sellers worldwide. We are seeking a Senior Data Scientist to join our central science team. As a Senior Data Scientist, you will apply Natural Language Processing (NLP), Large Language Models (LLMs), and econometrics to enhance our e-commerce marketplace. Join our team to leverage Amazon's resources, including comprehensive datasets and advanced technology, to make a significant impact on international seller growth and engagement.
Key job responsibilities
• Analyze seller data using advanced NLP techniques to extract actionable insights from feedback.
• Collaborate closely with scientists on development of AI-powered solutions
• Own and develop complex econometric models to measure and forecast the ROI of various investments and initiatives, partnering with economists to ensure robust methodologies
• Apply advanced machine learning and statistical techniques to solve intricate business problems
• Develop scalable, production-ready data science solutions that can be deployed across multiple international marketplaces
• Synthesize and communicate complex analytical findings and recommendations to senior leadership, influencing strategic decisions
• Mentor junior data scientists, fostering a culture of innovation and excellence within the team
• Stay at the forefront of data science advancements, continuously exploring and implementing new techniques to enhance our capabilities
• Collaborate cross-functionally with product managers, engineers, and business teams to translate data insights into actionable strategies
• Contribute to the broader Amazon data science community through knowledge sharing, best practices, and innovative methodologies
About the team
Our central science team is the analytical powerhouse driving Amazon's International Seller Growth organization. We're a diverse group of data scientists, machine learning experts, and economists united by our passion for leveraging data and technology to solve complex business challenges. Our work directly impacts millions of sellers worldwide and plays a crucial role in Amazon's global expansion strategy.
We pride ourselves on our culture of innovation, where we're constantly pushing the boundaries of what's possible with data science and AI. Our team enjoys high visibility and collaboration with senior leadership, providing ample opportunities to influence strategic decisions and drive impactful changes.
By joining our team, you'll be part of a community that values intellectual curiosity, embraces challenges, and is committed to making a large-scale impact through the power of data and science. Whether you're developing groundbreaking NLP models, crafting sophisticated econometric analyses, or pioneering new AI applications, your work will be instrumental in shaping the future of e-commerce and empowering sellers around the globe.
- 5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- 4+ years of data scientist experience
- Experience with statistical models e.g. multinomial logistic regression
- Master's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science
- 2+ years of data visualization using AWS QuickSight, Tableau, R Shiny, etc. experience
- Experience documenting modeling for technical and business leaders
- Experience as a leader and mentor on a data science team
- Experience working with scientists, economists, software developers, or product managers
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.