Beth Nganga

About Beth Nganga

Data & Business Intelligence Analyst with 9+ years of experience across banking, finance, and insurance industries at Ally Banking, Berkshire Hathaway, Capital One Financial, and Cognizant. Skilled in SQL, Power BI, and Snowflake, driving measurable improvements in data quality, automation, and reporting accuracy. Delivered 60% faster executive reporting through dynamic BI dashboards, 38% reduction in data latency via optimized ETL pipelines, and 29% fewer AML false alerts using analytics-driven monitoring. Expert in financial forecasting, credit risk modeling, and compliance reporting, translating business requirements into actionable insights and scalable data solutions that strengthen performance transparency and decision-making across enterprise environments.

Experience

1. Data Analyst Bi Developer

   Ally

   Jul 2023 — Present · TX, US

   Designed automated Power BI dashboards using DAX and SQL models, improving loan portfolio visibility across 15+ KPIs and reducing executive reporting turnaround from 4 days to 6 hours weekly- Integrated data from Redshift, Snowflake, and Salesforce via Airflow pipelines, cutting manual reconciliation time by 38% and enhancing financial forecast accuracy across lending and deposit domains- Conducted A/B testing on digital channel engagement using Python (Pandas, SciPy), increasing campaign conversion rates by 24% and optimizing ROI allocation across customer acquisition campaigns- Built SSIS-based ETL pipelines for credit card transaction monitoring, improving data refresh frequency from daily to hourly and supporting fraud detection model retraining with 17% faster processing speed- Collaborated with compliance and risk teams to automate AML and KYC analytics dashboards, reducing false-positive alerts by 29% and improving transaction review efficiency across 8 key business units- Designed data validation frameworks in SQL Server and Power BI to ensure 99.5% reporting accuracy, preventing metric drift across multi-source financial data environments- Optimized Snowflake data models by applying partitioning and clustering strategies, improving query performance by 44% and lowering monthly compute costs by 21%- Developed executive profitability dashboards with dynamic DAX measures, visualizing loan yields, customer churn, and product mix, enabling leadership to identify $3.2M in annual cost-saving opportunities- Implemented Python-based anomaly detection scripts for transaction trend monitoring, detecting deviations in high-risk segments with 96% detection precision and accelerating fraud response time by 35%.

Education

• Kenyatta University

  Bachelor of Arts - BA, Sociology