Megha W.

About Megha W.

Data Analyst with over 6 years of experience in data modeling, ETL development, statistical analysis, and dashboard reporting across finance, compliance, and enterprise analytics domains. Skilled in Python (Pandas, NumPy, SciPy), SQL (SQL Server, Hive), Power BI, Tableau, and Excel, with hands-on expertise in cloud platforms including AWS (Glue, Redshift) and Azure (Data Factory, Synapse, Purview). Proven ability to develop predictive models, automate data pipelines, and deliver executive-level insights to support risk mitigation, regulatory compliance, and data-driven decision-making. Strong understanding of Agile methodologies, data governance practices, and crossfunctional collaboration

Experience

1. Data Analyst

   Fifth Third Bank

   May 2023 — Present · US

   Architected predictive analytics pipelines using Python libraries (XGBoost, StatsModels, NumPy, Pandas) in Jupyter Notebook, enhancing model precision for loan default forecasting by 22% while minimizing false positives and supporting more robust credit decisions. Orchestrated end-to-end ETL processes using AWS Glue, Snowflake, AWS Redshift, and RESTful APIs, boosting operational pipeline throughput by 35% and enabling near real-time data synchronization for business intelligence applications. Applied unsupervised learning techniques including K-Means clustering and PCA via SQL Server to profile customer segments, uncovering high-risk borrower patterns and decreasing exposure to default-prone cohorts by 15%. Crafted executive-ready Power BI dashboards using advanced DAX measures, Power Query transformations, and Row-Level Security (RLS), equipping stakeholders with regulatory insights and compliance performance summaries. Investigated transactional trends through EDA, anomaly detection, and time series forecasting with Seaborn, SciPy, and Matplotlib, uncovering fraud indicators and bolstering AML investigative capabilities. Partnered within Agile teams alongside compliance experts, BAs, and data engineers to validate model interpretability via SHAP values and feature importance metrics, streamlining cross-functional data accuracy and audit preparedness.

Education

• Nagpur University

  Bachelor of Engineering (B.E.)

  2008 — 2012

• University of Cincinnati Carl H. Lindner College of Business

  Master of Arts (MA)

  2015 — 2016