Business Analyst I

Amazon Inc.; Hyderabad; On-site; INR 1,800,000 - 2,800,000; Full time

Job summary

Amazon FinOps is seeking a highly skilled Business Analyst to join the Collections Quality Control and Governance team. You will work with large datasets, influence analytics capabilities, and build AI-driven strategies to adapt to dynamic business environments.

You will collaborate with Product, Software Engineers and Data Engineers, develop data processing jobs in SQL/Python, and help deploy AI solutions that improve collections quality and operational efficiency.

Qualifications

• 4+ years building financial and operational reports/data sets that inform business decision-making.
• Knowledge of SQL or Python.
• 4+ years of relevant experience in BI, analytics, statistics, data engineering, data science, or related field.
• 2+ years building automations using AWS services like Lambda, S3, Glue, Redshift, QuickSight, EventBridge, Step Functions.
• 1+ years of experience in AI-based risk automation, quality control, anomaly detection, or defect prediction using self-serve AI tools.
• 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 and experience applying AI/ML libraries for business analytics.
• Knowledge of Excel, Access, Oracle, Essbase, SQL, and VBA.
• Good experience with engineering and operations best practices (version control, data quality/testing, monitoring).
• Excellent communication and data presentation skills.

Responsibilities

• Develop moderately to highly complex data processing jobs using SQL, Python, and other technologies.
• Leverage AI/ML algorithms for predictive analytics, anomaly detection, and pattern recognition in quality control data.
• Apply AI-driven text mining to identify critical business insights and optimize operations.
• Build forecasting models using AI/ML techniques for operational drivers and metrics.
• Develop risk scoring and health measurement by linking documents with tech controls and GRC controls.
• Collaborate with Product, Software Engineers and Data Engineers to integrate AI outputs into automated workflows.
• Actively manage timelines and deliverables of projects, anticipate risks, and resolve issues.
• Advise leaders on project milestones and prioritization; drive continuous improvement via AI automation.

Skills

SQL

Python

AWS

NLP

UiPath RPA

Data Visualization

Tools

AWS Lambda

S3

Glue

Redshift

SageMaker

EventBridge

Step Functions

Power BI

QuickSight

Tableau

Job description

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

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Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Veterans, military spouses, and people with disabilities are encouraged to apply.