Pulkeet Jani
About Candidate
Data Analyst with 6+ years of experience delivering data-driven insights within financial services at Capital One. Strong expertise in SQL, Python, Tableau, Snowflake, and AWS, with a proven record of building automated workflows, scalable dashboards, and risk analytics solutions. Known for translating complex datasets into actionable insights that improve operational efficiency, reduce risk exposure, and support executive decision-making.
Location
Education
Work & Experience
- Led analytics and data engineering initiatives focused on fraud prevention and risk monitoring across Zelle, Check Deposit, and Payment platforms. - Engineered automated prevention and risk-monitoring pipelines using AWP concepts, Google Apps Script, and Snowflake, increasing agent productivity (IPH) by 63%. - Designed and optimized ETL/ELT workflows using SQL, Python, Snowflake, Databricks, Azure, and AWS to support operational and risk analytics. - Built and maintained Tableau and Power BI dashboards for KPI tracking, agent scorecards, and performance monitoring used by managers and senior leadership. - Optimized Snowflake data models, joins, and governance scripts to improve data quality, reporting accuracy, and processing efficiency. - Migrated the legacy reporting scripts during enterprise-wide data source modernization initiatives.
- Designed, built, and maintained scalable ETL/ELT data workflows using SQL, Python, Snowflake, Databricks, Azure, and AWS to support fraud prevention, risk analytics, and operational reporting. - Conducted exploratory and root-cause analysis to identify trends, anomalies, and drivers impacting delinquency, fraud, and credit risk. - Supported Risk Events initiatives with time-sensitive analytics for monetary adjustments, high-balance reviews, delinquency analysis, mail-file creation, and campaign reporting. - Developed and maintained analytical controls using Python and PySpark; migrated legacy SQL workflows to Databricks to improve scalability and execution time. - Built and maintained Tableau and Power BI dashboards to support BAU reporting, KPI tracking, and operational decision-making.
- Collected, cleaned, and prepared structured datasets using Python, SQL, and Excel for analytics and reporting. - Performed exploratory and explanatory data analysis using Python (Pandas, Matplotlib, Seaborn) and Tableau to generate actionable insights. - Built forecasting and predictive models by transforming raw datasets into analysis-ready formats. - Validated, refactored, and modernized Python reporting scripts by replacing deprecated libraries.
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