Data Scientist, Amazon FinAuto - Lantern - Hyderabad, India

Are you passionate about building scalable solutions that transform how Amazonians work? Join us in revolutionizing Amazon's procurement technology through advanced analytics and machine learning. We are seeking a talented Data Scientist to help build the next generation of procurement applications from the ground up. This is an opportunity to work on high-impact systems combining advanced search, AI-powered assistance, and more.

About This Role

As a Data Scientist in the Global Corporate Procurement (GCP) Tech team, you will be instrumental in building modern, AI/ML-powered applications that transform Amazon's procurement systems. You will work on a greenfield initiative to create innovative solutions leveraging machine learning, natural language processing, and predictive analytics to make procurement faster, smarter, and more intuitive for Amazonians worldwide.

This role offers the unique opportunity to develop data-driven systems using AI/ML services, modern statistical modeling, and generative AI capabilities. You will collaborate with experienced data scientists, engineers, and cross-functional partners to deliver solutions for Amazon's global workforce.

What You'll Do

• Design, develop, and deploy scalable machine learning models and data pipelines that power Amazon's procurement ecosystem.
• Work in an agile environment, taking ownership of analytical solutions from conception through production deployment, contributing to technical decisions.
• Directly impact the daily experience of Amazonians as they procure goods and services.
• Translate complex business requirements into data-driven solutions using advanced analytics, NLP, and AI/ML techniques, collaborating with product managers, UX designers, and fellow data scientists.
• Use data analyses and statistical techniques to improve customer experience and guide business decision-making.
• Identify predictors and causes of business-related problems and implement novel approaches for forecasting and prediction.
• Identify, develop, manage, and execute analyses to uncover opportunities and present written business recommendations.
• Collaborate with multiple teams as a leader of quantitative analysis, developing solutions that adhere to the highest standards of analytical rigor and data integrity.
• Analyze and solve business problems at their root.

Basic Qualifications

• 1+ years of experience with data querying languages (e.g., SQL), scripting languages (e.g., Python), or statistical/mathematical software (e.g., R, SAS, Matlab).
• 2+ years of experience as a data/research scientist, statistician, or quantitative analyst in an internet-based company with complex and big data sources.
• 1+ years of experience creating or contributing to mathematical textbooks, research papers, or educational content.
• Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or equivalent work experience in a STEM field.

Preferred Qualifications

• Ph.D. in Science, Technology, Engineering, or Mathematics (STEM).
• Knowledge of statistical packages and business intelligence tools such as SPSS, SAS, S-PLUS, or R.
• Knowledge of machine learning concepts and their application to reasoning and problem-solving.
• Experience with clustered data processing (e.g., Hadoop, Spark, Map-reduce, and Hive).
• Experience working with or evaluating AI systems.
• Experience applying quantitative analysis to solve business problems and making data-driven business decisions.
• Experience effectively communicating complex concepts through written and verbal communication.

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.