AmazonPosted 3mo ago

Business Analyst I

Business Analyst I at Amazon scores 48 out of 100 on AI centrality, which makes it AI Level 2 of 4 (Uses AI) on this board. The level measures how much of the work is AI, not seniority.

IN, TS, Hyderabadmidfull-time

AI in this role

pytorchtensorflowscikit-learnsagemaker

ai-automationnlp

Amazon FinOps is seeking a highly skilled Business Analyst to join the Collections Quality Control and Governance team. As an analytics expert, you will work with some of the world's largest datasets, influence the evolution of our data analytics capabilities, and build AI-driven operational strategies to adapt and succeed in dynamic business environments.
You will be a key influencer on the team, providing input on priorities, understanding and anticipating stakeholder needs, and thinking big when recommending solutions. You will navigate ambiguous environments confidently, confirm assumptions, and advise leaders on project milestones and prioritization

Key job responsibilities
Data Analytics & AI-Powered Risk mitigation automations
• Develop moderately to highly complex data processing jobs using SQL, Python, and other technologies
• Leverage artificial intelligence and machine learning algorithms for predictive analytics, anomaly detection, and pattern recognition in quality control data
• Apply AI-driven text mining and data analytics to identify critical business insights and optimize operational efforts
• Build statistically robust forecasting models using AI/ML techniques for operational effort drivers and related metrics
• Build Risk identification, monitoring and automated mitigation actions using internal AI tools/MCP.
• Develop end-to-end AI solutions — data ingestion → model training → testing → deployment → monitoring
• Collaborating with Product, Software Engineers and Data Engineers to integrate AI outputs into automated workflows

Quality Control & Governance
• Build accurate dashboards to track operational metrics including KPIs, process/channel/team specific goals for collections quality
• Analyze customer behavioral patterns and process data to identify defect trends and quality improvement opportunities
• Investigate data anomalies, understand root causes, and develop alternative measurement strategies
• Present historical data trends and operational statistics in meaningful, insightful, and actionable formats
• Develop controllership risk scoring and health measuring system by connecting Policy/SOP/Official documents with tech controls and operational GRC Controls.

Stakeholder Collaboration & Business Intelligence
• Collaborate with stakeholders to understand business domains, requirements, and expectations in collections quality operations
• Support Global FinOps teams on business reporting, ad hoc analysis, statistical inference, and predictive modeling
• Work with data source system owners to understand capabilities and limitations
• Map and relate data to business operations with strong data interpretation skills

Project Management
• Actively manage timelines and deliverables of projects, anticipate risks, and resolve issues
• Advise leaders and stakeholders on project milestones and associated prioritization
• Drive continuous improvement initiatives leveraging AI automation and advanced analytics

Basic qualifications

- 4+ years of building financial and operational reports/data sets that inform business decision-making experience
- Knowledge of SQL or Python
- • 4+ years of relevant professional experience in business intelligence, analytics, statistics, data engineering, data science, or related field
- • 2+ years of relevant experience in building automations using AWS services like AWS Lambda, S3, Glue, Redshift, QuickSuite, EventBridge, Step Function etc.
- • 1+ years of experience in building AI based risk automation, quality control, anomaly detection, or defect prediction using self-serve AI tools. Knowledge of AI-powered automation tools and frameworks.
- • Experience with data modeling, SQL, ETL, data warehousing, and data lakes with specialist-level SQL proficiency.
- • Experience with API integrations for reading data from applications and feeding into AI/LLM for insights/actions.
- • Proficiency with Python (Mandatory) and experience applying AI/ML libraries for business analytics.
- • Knowledge of standard software including Excel, Access, Oracle, Essbase, SQL, and VBA
- • Good experience with engineering and operations best practices (version control, data quality/testing, monitoring)
- • Excellent verbal/written communication and data presentation skills, with ability to summarize key findings and communicate effectively with both business and technical teams
- • 2+ years of participating in continuous improvement projects with measurable results
- • 2+ years’ experience of RPA development using UiPath (Expert level)
- • Background in collections, accounts receivable, or financial operations quality assurance
- • Experience with natural language processing (NLP) for text analytics
- • Familiarity with statistical modeling and predictive analytics platforms
- Technical Skills
- • AWS cloud services (Lambda, Glue, Redshift, S3, SageMaker, EventBridge, Step Function)
- • AI/ML frameworks and libraries (scikit-learn, TensorFlow, PyTorch, etc.)
- • Data visualization tools (QuickSight, Tableau, Power BI)
- • Statistical analysis and predictive modeling
- • ETL processes and data pipeline development

Preferred qualifications

- 2+ years of participating in continuous improvement projects in your team to scale and improve controllership with measurable results experience
- • 2+ years’ experience of RPA development using UiPath (Expert level)
- • Background in collections, accounts receivable, or financial operations quality assurance
- • Experience with natural language processing (NLP) for text analytics
- • Familiarity with statistical modeling and predictive analytics platforms
- Technical Skills
- • Advanced SQL and Python programming
- • AWS cloud services (Lambda, Glue, Redshift, S3, SageMaker, EventBridge, Step Function)
- • AI/ML frameworks and libraries (scikit-learn, TensorFlow, PyTorch, etc.)
- • Data visualization tools (QuickSight, Tableau, Power BI)
- • Statistical analysis and predictive modeling
- • ETL processes and data pipeline development

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.

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

AI AutomationNlpPyTorchTensorFlowscikit-learnSagemaker

Questions you could be asked

Tell me about a workflow you automated with AI tools, end to end.
What NLP problem have you worked on, and how did you measure whether it actually worked?
What are the limits of PyTorch that you've run into, and how did you work around them?
What's a project where you used TensorFlow hands-on?
Walk me through how you've used scikit-learn in your day-to-day work.

Adapt your resume

List these exact terms on your resume: AI Automation, Nlp, PyTorch, TensorFlow, and scikit-learn. 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.
Put the AI tool in a bullet point about what you did, not just in a skills list — this role treats it as a required part of the job.

Want your resume actually rewritten for this job?

The free preview above is everything we have today. A full resume rewrite is not live yet and has no price set. Join the waitlist and we will email you if we open it.