Business Intelligence Engineer II, AOP

Amazon is hiring a Business Intelligence Engineer II, AOP in Gurugram, India. Level rates it ; you can apply on Amazon.

Level's read on this job

On Level's scale, this role is Works on AI ●●●○: the daily work is on AI products, without building the model.
Tools and skills the posting cites include AI evaluation, data engineering and statistical analysis.
Level classifies it as a mid-level role.
Level lists 20,000+ other open roles at Amazon.

AI in this role

Own, monitor, and enhance machine learning and operations research models to drive cost savings across Amazon's supply network.

ai-evaluationdata-engineeringstatistical-analysismodel-evaluationsql

Amazon strives to be Earth's most customer-centric company where people can find and discover virtually anything they want to buy online. By giving customers more of what they want - low prices, vast selection, and convenience - Amazon continues to grow and evolve as a world-class e-commerce platform. The AOP team is an integral part of this and strives to provide Data and Science Capabilities to fulfill all customer processes in the APAC, LATAM, IN and MENA Ops businesses.

This BIE role sits at a rare intersection and has high growth prospects. On one side, you have cutting-edge ML/OR models making split-second cost saving decisions across Ops network. On the other, you have the analytical depth required to understand why those models succeed, where they fall short, and what needs to change. You won't just be observing these models from the outside — you'll own them along with the Scientists. Their performance, their enhancements, their evolution over time — that's your responsibility. When the model needs a new feature, a re-calibrated threshold, or a fundamentally different approach to a particular corridor or condition, you're the one driving that forward in partnership with the scientists who built it. In some instances you will also directly own these models.

The technical challenges here are genuinely complex and rewarding. You'll work with large-scale, low-latency data flowing through real-time pipelines. You'll design automated reporting frameworks that need to be as robust as the system they monitor. You'll apply statistical rigor to evaluate model performance in production, design experiments to validate enhancements, and quantify impact in an environment where conditions shift daily. But beyond monitoring, you'll be the one identifying what's broken, proposing what to build next, and owning the analytical path from hypothesis to deployed improvement. This is a role without a single well-worn toolkit, you'll have the opportunity to continuously sharpen your skills across data engineering, statistical analysis, and model evaluation to keep pace with the problems in front of you.

What makes this role particularly compelling is the combination of ownership and impact. The products you will work on drive millions in cost savings for Amazon Ops. You will also be involved in cutting-edge research. You'll need to be comfortable with ambiguity. Many of the most important questions in this space haven't been cleanly articulated yet — they emerge from patterns in the data, from model behavior that doesn't match expectations, from edge cases that only surface under certain network conditions. You'll need strong statistical foundations, fluency in SQL and Python and AWS Services, and experience building scalable BI solutions. Your ability to move between deep technical analysis and clear stakeholder communication — and to own outcomes end-to-end rather than just deliver reports — is what will make you exceptional in this role.

About the team
The AOP Science Team is the central science team of Amazon APAC, LATAM, IN and MENA Operations. We are responsible for creating core science capabilities to scale decision making across domains such as Truck Capacity Optimization, Short-term capacity planning, Network Abuse Detection, Impact analyses, Productivity improvement Models and so on. As a team our goal is to support our customers to make better decisions by leveraging applied statistics, machine learning, OR, deep learning architecture and algorithms. Team owns end-to-end life cycle for science model development which includes data exploration, experimentation, automating near real-time data pipelines, data visualization and model productionization.

Basic qualifications

- 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- Experience with data visualization using Tableau, Quicksight, or similar tools
- Experience with data modeling, warehousing and building ETL pipelines
- Experience in Statistical Analysis packages such as R, SAS and Matlab
- Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling

Preferred qualifications

- Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift
- Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets

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 Intelligence Engineer II, AOP at Amazon rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

●●●● 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.

Key facts

Business Intelligence Engineer II, AOP is an open job at Amazon.
Level rates this role AI Level 3 of 4: Works on AI.
The role is based in IN, HR, Gurugram.
The job was posted on July 2, 2026.
Seniority: mid.
Applications are handled by Amazon. Apply on Amazon

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

AI EvaluationData EngineeringStatistical AnalysisModel EvaluationSQL

Questions you could be asked

How do you decide that one model's output is better than another's for a given task?
Tell me about a project where data engineering was part of your work. What did you do?
Tell me about a project where statistical analysis 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?
Tell me about a project where sql was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: AI Evaluation, Data Engineering, Statistical Analysis, Model Evaluation, 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.
Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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