Business Analyst Support, AOP Research Science

Amazon is hiring a Business Analyst Support, AOP Research Science in Bengaluru, India. Level rates it ; you can apply on Amazon.

Level's read on this job

On Level's scale, this business analyst role is Little AI ●○○○: aI is not part of the work.
Level classifies it as a mid-level role.
Level lists 20,000+ other open roles at Amazon.
The role was posted in the last few days.

AI in this role

The candidate would be responsible for creating/maintaining complex SQL queries and scheduling/refreshing ETL jobs. They would be required to automate manual tasks and simplify them using Python. They would also be required to build data pipelines/dashboards, take up dive deep requests, make changes to existing analytical framework and provide data support to concerned stakeholders. The person should have a good understanding of a business requirement and the ability to quickly get to the root cause of a particular reporting/BI/data issue and draft solutions for resolution specially during high demand period like OP/3YF planning. The ideal candidate would be high on attention detail, show bias for action and keen interest in analytics/BI/automation.

Some of the key result areas include, but not limited to:

Own the design, development and maintenance of ongoing data pipelines, queries, metrics, reports, analyses, dashboards, etc. to drive key business decisions. Ensure data accuracy by validating data for new and resources.
Work closely with stakeholders (internal/external) to understand and automate/enhance the existing processes.
Should be open to learn and develop skillsets in the latest data and AWS technologies and analytical techniques
Should be able to solve a business problem through a solution driven by data.
Should be able to come up with innovative ideas for new work or to improve existing work.

Key job responsibilities
- Monitor the health of the team's production models and pipelines, and run recurring executions on schedule (e.g., periodic model runs, data refreshes, reporting cadences).

- Perform first-level troubleshooting of pipeline and model-run failures — diagnosing common issues (data quality, missing inputs, job failures) and resolving them with minimal guidance, escalating deeper modeling issues to the OR scientists with clear, well-documented context.

- Maintain run documentation, runbooks, and operational trackers so execution is consistent and repeatable.

- Validate inputs and outputs for each run, flagging anomalies before they reach stakeholders.

A day in the life
You are the operational backbone that keeps our optimization models running reliably. Your day starts with health-checks on production runs — validating inputs/outputs and first-level troubleshooting of failures, resolving common issues with minimal guidance and escalating deeper modeling questions to the OR scientists. The rest of your time goes to BI work: complex SQL, Python automation, pipelines, dashboards, and dive-deep requests. You partner with Research Scientists, BIEs, and Program/Product Managers, serving supply-chain planning teams across ROW markets — with stakes peaking during OP/3YF planning cycles where accuracy and fast turnaround matter most.

About the team
The GSARC-AOP (Analytics Operations & Programs) Research Science team builds and operates decision-support and optimization products across Network Design, Quick Commerce, and Packaging for Amazon's Rest of World (ROW) marketplaces — spanning multiple OR tools. We are looking for a Business Analyst to be the operational backbone of this portfolio: keeping our production models healthy and running, and contributing hands-on analytics and BI work that supports the team's decision-making.

This is a high-ownership execution role for an analyst who is energized by reliability, likes working close to data and models, and wants to grow their technical depth alongside a team of Operations Research scientists and Business Intelligence Engineers for the multiple geographies like IN, Japan, Mexico, Brazil, MENA, AU

Basic qualifications

- 2+ years of data analytics or automation experience
- Experience with data mining tools like SQL, SAS, SPSS, or similar
- Bachelor's degree or above in engineering, statistics, computer science, mathematics, or a related quantitative field
- Experience that includes strong analytical skills, attention to detail, and effective communication abilities, or experience working with customers with a passion for delivering exceptional service and experience with automation and any version control tools

Preferred qualifications

- Knowledge of data pipelining and extraction using SQL
- Experience troubleshooting and debugging technical systems, or experience that includes strong analytical skills, attention to detail, and effective communication abilities and experience with automation and any version control tools
- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
- Master's degree, or a Bachelor's degree and experience building web based dashboards using common frameworks
- Bachelor's degree in operations, supply chain or logistics, or 2+ years of managing, analyzing and communicating results to senior leadership experience

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 Analyst Support, AOP Research Science at Amazon rates 25 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.

●●●● 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.