Ap Quality Control Business Analyst I, Accounts Payable Quality Control

Amazon Amazon · Big Tech · IN, TS, Hyderabad · Finance & Accounting

This role involves developing and deploying end-to-end AI solutions for quality control and risk mitigation in financial operations. The analyst will use SQL, Python, and AWS services to build predictive models, anomaly detection systems, and automated mitigation actions. Key responsibilities include data ingestion, model training, deployment, monitoring, and collaborating with engineering teams to integrate AI outputs into automated workflows. The role also involves building dashboards, analyzing customer behavior, and presenting insights to stakeholders.

What you'd actually do

  1. Develop moderately to highly complex data processing jobs using SQL, Python, and other technologies
  2. Leverage artificial intelligence and machine learning algorithms for predictive analytics, anomaly detection, and pattern recognition in quality control data
  3. Apply AI-driven text mining and data analytics to identify critical business insights and optimize operational efforts
  4. Build statistically robust forecasting models using AI/ML techniques for operational effort drivers and related metrics
  5. Build Risk identification, monitoring and automated mitigation actions using internal AI tools/MCP.

Skills

Required

  • Advanced SQL
  • Advanced 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
  • API integrations for reading data from applications and feeding into AI/LLM for insights/actions.

Nice to have

  • RPA development using UiPath
  • Natural language processing (NLP) for text analytics
  • Statistical modeling and predictive analytics platforms

What the JD emphasized

  • Minimum 1 year of experience in building AI based risk automation, quality control, anomaly detection, or defect prediction using self-serve AI tools.
  • Experience with AI/ML technologies
  • Proficiency with Python (Mandatory)

Other signals

  • Develop end-to-end AI solutions — data ingestion → model training → testing → deployment → monitoring
  • Leverage artificial intelligence and machine learning algorithms for predictive analytics, anomaly detection, and pattern recognition in quality control data
  • Build Risk identification, monitoring and automated mitigation actions using internal AI tools/MCP.