Ameya Dighe

Designed and rolled out a real-time Validation Framework using Python across three systems, improving central trade repository data accuracy by 25% month-on-month and detecting issues 4.5 hours earlier. Led automation of reconciliations and integrated GitHub Copilot to improve code quality and shorten delivery timelines by 20%.

Automated data workflows and cleansing with Python and Git, reducing manual intervention by 40% and increasing process efficiency. Led workshops and partnered with data consumers (including Volcker teams) to align quality requirements and cut manual overrides by 40% prior to regulatory submissions.

Implemented data quality controls and reconciliation processes using Python and SQL, achieving 95% data accuracy and reducing errors by 20%. Led BAU support and automation efforts that cut data breaks by 75% and delivered 100% automation of break analysis.

Conducted business process analysis for Critical Inventory Logistics during a major acquisition, streamlining processes to ease system consolidation. Evaluated Sparx EA and Oracle BPA tools and produced a qualitative assessment to support tool selection.

Performed deep-dive data analysis in Excel and coordinated offshore teams to reduce incident count by 30% and accelerate issue resolution. Designed complex SQL queries and stored procedures to improve customer satisfaction reporting, maintaining a CSI of 4.8/5.

Completed a Master of Science in Management Information Systems at Texas A&M University (Aug 2014—Jun 2016).

Completed a Bachelor of Engineering in Computer Engineering at Vivekanand Education Society's Institute of Technology (Jul 2008—Jun 2012).