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Business Research Analyst - I, RBS Tech
AI in this role
Implement and evaluate machine learning models and LLM-based inferences for Amazon's retail business systems.
PythonSQLMachine learningLLM
prompt-engineeringmachine-learningmodel-evaluation
Key job responsibilities
* Implement machine learning models (classical ML covering classification and regression models) using Python and ML frameworks
* Develop and iterate prompts for LLMs using few-shot, CoT, and instruction-based techniques
* Conduct offline evaluations and benchmarking / testing on LLM and ML outputs
* Collaborate with engineers to deploy models in production and monitor performance
* Document experiments and results; participate and brief milestones in weekly sprint planning and model reviews
Expectations
* Demonstrates hands-on skills in Python and ML/LLM toolkits
* Understands trade-offs between Generative AI vs. Machine Learning approaches
* Can deliver scoped ML components with guidance
* Effective communicator and team collaborator
About the team
The Retail Business Systems (RBS) group is an integral part of Amazon online product lifecycle and buying operations. The team is designed to ensure Amazon remains competitive in the online retail space with the best catalog quality, wide selection, supply chain defects and compliance programs. The team’s primary role is to create and enhance retail selection on the worldwide Amazon online catalog. The tasks handled have a direct impact on customer buying decisions and online user experience.
Basic qualifications
- Bachelor's degree
- Bachelor's degree in Quantitative or STEM disciplines (Science, Technology, Engineering, Mathematics)
- Relevant experience in solving real world business problems using AI/ML or applying GenAI and LLMs through prompt engineering techniques.
- Strong hands-on programming skills in Python, SQL.
- Strong analytical thinking
- Ability to creatively solve business problems, innovating new approaches where required and articulating ideas to a wide range of audiences using strong data, written and verbal communication skills
- Ability to collaborate effectively across multiple tech and business teams.
- PREFERRED QUALIFICATIONS
- Diverse experience will be favored eg. a mix of experience across different roles - In-depth understanding of machine learning concepts including developing models and tuning the hyper-parameters, as well as deploying models and building ML service - Technical expertise, experience in AI/ML and GenAI.
Preferred qualifications
- Knowledge of data modeling and data pipeline design
- Experience with statistical analysis, co-relation analysis
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
Business Research Analyst - I, RBS Tech at Amazon rates 90 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.
Classification
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. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Prompt engineeringMachine learningModel EvaluationPythonSQLLLM
Questions you could be asked
- How do you structure and test a prompt to get consistent output from a language model?
- Tell me about a project where machine learning was part of your work. What did you do?
- Tell me about a project where model evaluation was part of your work. What did you do?
- What's a project where you used Python hands-on?
- Walk me through how you've used SQL in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: Prompt engineering, Machine learning, Model Evaluation, Python, and SQL. 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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