Business Analyst I

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, - 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