The EU Amazon Vendor Services (AVS) and WW Vendor Experience (VX) Program teams are looking for a Data Scientist to help solve cutting-edge applied AI and ML solutions that will power our Voice of Vendor (VoV) program and address major challenges contributing to our vendors' success and increased satisfaction.

Amazon strives to be Earth's most customer-centric company, where customers can find and discover anything they might want to buy online. By providing customers with low prices, vast selection, and convenience, Amazon continues to grow as a world-class e-commerce website. Core to Amazon's mission to delight and serve customers is the need to invent on behalf of vendors. The EU AVS program aims to provide an industry-leading account management service at the optimal cost-to-serve for Amazon that exceeds vendors' expectations and expedites their growth on Amazon. The WW VX program vision is to make Amazon the most preferred, trusted, and efficient distribution option for vendors by building an industry-leading experience for every vendor across all global touchpoints.

Key job responsibilities:

• This role will sit in a data and analytics (DNA) team that supports two large program teams (EU AVS and VX), directly working with 15+ product managers.
• As a key member of the DNA team, you will leverage advanced analytics, machine learning, and AI to solve complex business problems and enhance vendor experiences.
• You will lead the development of machine learning and AI solutions that empower our global Voice of Vendor program to identify business areas (Listing, Ordering, Payments) that have the biggest impact on overall vendor satisfaction.
• You will provide meaningful vendor sentiment & anecdotes summaries to all partner teams using LLMs.
• You will develop models to identify the drivers of poor vendor feedback and take corrective and proactive actions to avoid this in the future.
• Every solution you build will need to be production-ready.
• Working closely with both PMs and PM-Ts, you will be involved in the end-to-end product feature development process from conception to productionisation.

BASIC QUALIFICATIONS

• At least a Master's degree in computer science, physics, statistics, mathematics, or a similar quantitative discipline.
• 5+ years of experience in using multiple data science methodologies to solve complex business problems.
• Experience as a data scientist, applied scientist, research scientist, or equivalent role.
• Experience with theory and practice of data science, machine learning, and artificial intelligence.
• Experience with data scripting languages (e.g., SQL, Python, R) and statistical/mathematical software (e.g., R, SAS, or Matlab).
• Expertise in SQL, data modeling, warehousing, and building ETL pipelines.
• Experience with AWS technologies (e.g., Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions).
• Knowledge of software engineering best practices and version control systems.
• Excellent ability to communicate with technical and non-technical stakeholders alike in written documents and verbal communication to collect data requirements.

PREFERRED QUALIFICATIONS

• Hands-on experience in Natural Language Processing (NLP) and leveraging Large Language Models (LLMs) for real-world NLP applications.
• Experience in working on the entire lifecycle of a data product, from conceptualization to productionisation.
• E-commerce experience.

Amazon is an equal opportunities employer. We believe that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify, and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice to know more about how we collect, use, and transfer the personal data of our candidates.

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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 our accommodations page for more information.

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