Jerusalem Derbew

About Jerusalem Derbew

Business Data Analyst | Fraud Risk Analyst | Data Analyst — 3 Years of Experience | Actively Seeking Opportunities I specialize in fraud risk analytics and data-driven decision-making within enterprise banking environments, combining strong SQL and Python capabilities with business analysis expertise to turn complex transactional data into operational intelligence. Core Expertise My work spans end-to-end analytics delivery — from data ingestion and transformation to executive reporting and stakeholder alignment. I\'m proficient in SQL (CTEs, Window Functions, Query Optimization), Python (Pandas, NumPy), Power BI (DAX, Power Query), Tableau, and Snowflake, with hands-on experience in AWS Glue, Azure Data Factory, and ETL pipeline development. On the business analysis side, I work across BRD, FRD, RTM, and Acceptance Criteria documentation within Agile and SDLC frameworks. Work Impact & Scale At JPMorgan Chase, I\'ve analyzed 12M+ transactions, reduced alert investigation cycles, supported $1.3M in loss avoidance decisions, and delivered 12 production analytics enhancements across fraud risk and compliance functions. I\'ve built ML anomaly detection integrations, led Champion Challenger testing across 4 consumer banking products, and automated intake workflows that cut onboarding time significantly. My project work includes unsupervised outlier detection on 2.8M healthcare claims and fraud model drift monitoring with regulatory validation support. Domain Context Primary experience in financial services (fraud risk, dispute resolution, compliance analytics) with applied project exposure in healthcare claims analytics. Keywords: Business Data Analyst OR Fraud Risk Analyst OR Data Analyst OR Business Analyst OR Analytics Engineer Core Skills: Business Analysis | SQL | Tableau | Power BI | Talend (ETL)| Process Re-engineering (AS-IS/TO-BE)| Agile/Scrum (Jira/Confluence)| UAT & Defect Management | Stakeholder Engagement | Data Storytelling | Requirements Gathering (BRD/FRD)| Pharmaceutical & Healthcare Insurance Domains Tools & Technologies: Snowflake, AWS Glue, Amazon S3, Azure Data Factory, SQL Server, Oracle, PostgreSQL, Jira, Confluence, Visio, Microsoft Excel, Appian, Scikit-learn, Power Query Concepts & Capabilities: Fraud Analytics, Risk Monitoring, BRD, FRD, RTM, Agile, SDLC, UAT, BPMN 2.0, Root Cause Analysis, Champion Challenger Testing, ML Model Monitoring, Data Governance, GDPR, HIPAA, CAMS, KPI Development, Stakeholder Management, Process Mapping

Experience

1. Business Data Analyst

   JPMorganChase

   May 2023 — Present · Dallas, TX, US

   Developed fraud analytics datasets using SQL (CTEs, Window Functions) on Snowflake and Python (Pandas) for feature-level analysis across 12M+ transactions, reducing alert investigation time to 2.4 days per case cycle. Designed executive-ready Power BI dashboards (DAX, Power Query) sourced from curated Snowflake data layers, enabling 7 fraud risk managers to prioritize high-risk alerts and support $1.3M in validated loss avoidance decisions. Performed controlled Champion Challenger testing using Statistical Analysis and Hypothesis Testing, refining 9 fraud detection thresholds across 4 consumer banking products while stabilizing alert volumes. Built ingestion and transformation workflows in AWS Glue (ETL) feeding into Snowflake, eliminating 8 reconciliation tasks and strengthening data quality checks across 16 upstream feeds. Integrated Machine Learning (ML) anomaly detection outputs into fraud monitoring dashboards, improving query retrieval time to 4 seconds for operational risk reviews. Authored BRD, FRD, and Acceptance Criteria within Agile (Jira, Confluence) ceremonies, coordinating 6 cross-functional teams and delivering 12 production-ready analytics enhancements over 18 months. Executed Root Cause Analysis using BPMN 2.0 process mapping (Visio) to remediate 8 validated bottlenecks, improving stability across fraud investigation queues and dispute resolution workflows. Coordinated UAT support, Acceptance Criteria validation, and Requirement Traceability Matrix (RTM) tracking in Jira, limiting post-release defect tickets to single-digit counts per deployment cycle. Supported Appian workflow automation integrated with SQL Server backend systems, digitizing 7 intake processes and reducing onboarding time to 3 hours per submission. Developed interactive Tableau dashboards for fraud intake monitoring with drill-downs and parameter controls, enabling self-service analytics for compliance and risk teams.

Education

• University of North Texas

  Bachelor of Science, Information Science - Data Science / Minor in Business

• Dallas College

  Associate of Science - AS, Business/Commerce, General

• University of North Texas

  Master of Business Administration - MBA, Business Analytics