Posted 21 July, 2026
AP Quality Control Business Analyst I, Accounts Payable Quality Control
Amazon
IN, TS, Hyderabad
Full Time
Reference: 71_457715_646974ec-6567-4861-b494-446b5f60036b
Amazon FinOps is seeking a highly skilled Business Analyst to join the AP Quality Control 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
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
Basic Qualifications
4+ years of building financial and operational reports/data sets that influence business decision-making
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.
Minimum 1 year 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
Preferred Qualifications
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
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
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
Basic Qualifications
4+ years of building financial and operational reports/data sets that influence business decision-making
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.
Minimum 1 year 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
Preferred Qualifications
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