Data Scientist II, Amazon FinAuto - Lantern
AI in this role
Are you passionate about building scalable solutions that impact how Amazonians get their work done? Join us in revolutionizing Amazon's procurement technology landscape through advanced analytics and machine learning.
We're seeking a talented Data Scientist to help build the next generation of procurement applications from the ground up. This is your opportunity to work on high-impact systems that combine advanced search capabilities, AI-powered assistance.
About This Role
As a Data Scientist in the Global Corporate Procurement (GCP) Tech team, you'll be instrumental in building modern, AI/ML-powered applications that transform Amazon's procurement systems. You'll work on a greenfield initiative to create innovative solutions leveraging machine learning, natural language processing, and predictive analytics that make procurement faster, smarter, and more intuitive for Amazonians worldwide.
This role offers the unique opportunity to develop data-driven systems leveraging AI/ML services, modern statistical modeling techniques, and generative AI capabilities. You'll collaborate with experienced data scientists, engineers, and cross-functional partners to deliver solutions that will eventually serve Amazon's global workforce.
What You'll Do
You'll design, develop, and deploy scalable machine learning models and data pipelines that power Amazon's procurement ecosystem. Working in an agile environment, you'll take ownership of analytical solutions from conception through production deployment, contributing to technical decisions alongside experienced data scientists and engineers.
Your work will directly impact the daily experience of Amazonians as they procure goods and services. Through collaboration with product managers, UX designers, and fellow data scientists, you'll translate complex business requirements into elegant data-driven solutions using advanced analytics, NLP, and AI/ML techniques.
Key job responsibilities
* Use data analyses and statistical techniques to develop solutions to improve customer experience and to guide business decision making
* Identify predictors and causes of business-related problems and implement novel approaches related to forecasting and prediction
* Identify, develop, manage, and execute analyses to uncover areas of opportunity and present written business recommendations
* Collaborate with multiple teams as a leader of quantitative analysis and where you develop solutions that utilize the highest standards of analytical rigor and data integrity
* Analyze and solve business problems at their root
Basic qualifications
- 2+ years of data scientist experience
- 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
- 1+ years of guiding and coaching a group of researchers experience
- 1+ years of working with or evaluating AI systems experience
- 1+ years of creating or contributing to mathematical textbooks, research papers, or educational content experience
- Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)
- Experience applying theoretical models in an applied environment
Preferred qualifications
- Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)
- Knowledge of machine learning concepts and their application to reasoning and problem-solving
- Experience in Python, Perl, or another scripting language
- Experience in a ML or data scientist role with a large technology company
- Experience in defining and creating benchmarks for assessing GenAI model performance
- Experience working on multi-team, cross-disciplinary projects
- 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.
How we rate this
Data Scientist II, Amazon FinAuto - Lantern at Amazon rates 95 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- What NLP problem have you worked on, and how did you measure whether it actually worked?
- How would you decide a model or AI system is ready to ship?
- Tell me about a time a model underperformed in production. How did you find out, and what did you change?
Adapt your resume
- List these exact terms on your resume: NLP. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.
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