Mahek Gangadia

Data Analyst @Morgan Stanley

MA, US

Engineered predictive fraud-detection models with Python and Scikit-learn, integrating anomaly detection algorithms that reduced false negatives by 25% and strengthened compliance with financial regulatory standards. Architected scalable ETL pipelines using PySpark and Apache Airflow on Azure Databricks, compressing data ingestion latency by 30% and enabling near-real-time insights for high-volume trading datasets. Designed enterprise-wide Power BI dashboards with advanced DAX and row-level security, delivering self-service analytics to 500+ stakeholders and increasing executive reporting efficiency by 35%. Deployed clustering models for customer risk profiling, leveraging K-means and DBSCAN to enhance credit risk stratification and improve portfolio monitoring accuracy. Directed A/B and multivariate testing for digital product enhancements, applying statistical rigor to optimize conversion funnels and increasing user engagement by 20%. Spearheaded integration of cross-cloud platforms (AWS + GCP) to support large-scale distributed analytics, enabling scalable data storage, governance, and cost-efficient computation.

University of Mumbai

Bachelor of Engineering, Information Technology

Northeastern University

Masters of Science, Information Technology