Jay Trivedi
Technical Program Manager || Project & Program Management || Infrastructure || AI platforms || Distributed Systems || Cloud || Business Analytics || Professional Services. H1B holder.
- Role
- Senior Technical Consultant at Fannie Mae
- Location
- New York, NY, US
- LinkedIn followers
- 500 followers
About Jay Trivedi
Dynamic IT Consultant, Business Analyst, and Data Scientist with 6+ years of experience in IT implementation, professional services, software development, and data analytics across banking, finance, and healthcare industries. Skilled in delivering end-to-end technology solutions, streamlining IT infrastructure, and driving data-driven decision-making to enhance business performance. Expertise in full-stack software development (Python, C#.NET, SQL, Java), data science (Machine Learning, AI, Power BI), and cloud computing (AWS, Azure). Adept at analyzing business requirements, optimizing IT systems, integrating APIs, and automating workflows to improve operational efficiency and scalability. Proven track record of leading cross-functional teams, managing enterprise IT projects, and implementing data-driven solutions that reduce costs and drive digital transformation. Passionate about bridging the gap between business and technology by leveraging data analytics, software development, and IT consulting to create scalable, impactful solutions.My VISA status is active H1B since October 2024.GitHub Profile: Jay-t14
Experience
Senior Technical Consultant
Sep 2025 — Present · Reston, VA, US
Serve as lead analyst for enhancements within the AWS-hosted Single-Family Mortgage Data Utility (SMDU),coordinating business stakeholders, engineering, and QA teams to deliver validated data solutions supporting enterprisereporting across a $3.6T mortgage portfolio.Impact: Improved traceability between business rules and downstream reporting logic, reducing rework and improvingdelivery predictability.• Led end-to-end requirements lifecycle including elicitation, data mapping, user story authoring, acceptance criteriadefinition, and validation documentation.Impact: Increased clarity of technical implementation and reduced ambiguity-driven defects during sprint execution.• Directed complex SQL and Python-based reconciliation efforts to identify systemic data discrepancies across multiplesource systems.Impact: Strengthened data integrity and reduced recurring validation issues impacting reporting accuracy.• Coordinated controlled testing and production release activities, aligning technical teams with defined validationcheckpoints.Impact: Improved release stability and reduced post-deployment issue escalation.• Performed structured root cause analysis for high-impact data defects and documented corrective actions.Impact: Prevented repeat failures and improved system reliability over subsequent release cycles.
Education
K. J. Somaiya College of Engineering
BE - Bachelor of Engineering, Electronics
2011 — 2015
Rutgers Business School
Masters of Science, Information Technology and Analytics
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