Aman Vatsyayan

Strategic Data Analytics & AI Leader with 18+ years of progressive experience across Banking, Insurance, and Life-Sciences, specializing in data analytics, data quality and governance, and enterprise-scale analytical operations. Proven track record leading and developing managers and distributed teams to build high-performing, cross-functional analytics capabilities that deliver quality insights, remediation, and regulatory-compliant data operations for global stakeholders with strong ownership of quality, timeliness, and accuracy across service commitments. Expertise in SAS, SQL, Python, relational databases, BI platforms (Tableau, Power BI), statistical modeling, Data science and process automation.

Skilled at translating complex data challenges into actionable business insights, driving operational excellence through process improvement, automation, and stakeholder engagement across business, analytical, and technology functions. Seasoned people leader with a strong record of team building, coaching, and scaling high-performing analytics teams, and aligning team objectives with departmental strategy. Holds EPLM from IIM Calcutta, PMP training, and certifications in PSM I (Professional Scrum Master), DevOps Fundamentals, Microsoft Azure Fundamentals, and Microsoft Azure AI Fundamentals — reflecting curiosity and enthusiasm for Generative AI, Agentic AI, and cloud platforms in driving process efficiency.

VP - Analytics Manager at Wells Fargo (2022-12 – Present)

• Established Customer Remediation Analytics team and own end-to-end delivery of data operations and analytical support for enterprise-wide customer remediation programs across multiple Lines of Business (Home Lending, Credit Card, Auto Lending etc.) — ensuring 100% accuracy, regulatory compliance, and on-time delivery of commitments to senior stakeholders and audit team
• Analyzed, validated and delivered ~180 customer remediation verification reviews over 3 years — ensuring the right impacted customers received refunds (~USD $2 Billion+ in compensation) and non-financially impacted customers' credit ratings were correctly updated with credit bureaus, covering 50,000+ impacted customers in compliance with regulatory requirements
• Drive operational excellence through process improvement and automation — engineering and deploying solutions using SAS, SQL, and Python that reduced analytical turnaround time by 30%, enabling the team to scale capacity without additional headcount. Automation framework using Python that converted manual tasks into fully automated validation logic which reduced processing time from 30 days to 30 minutes (99.93% improvement) while enhancing accuracy and eliminating manual errors
• Establish team priorities, allocate resources, and monitor performance against operational objectives and service commitments via a robust data quality and governance framework — encompassing automated validation checks, reconciliation logic, and structured peer-review protocols — achieving a 40% reduction in data issues and strengthening audit readiness
• Implemented a RAG and AI Agent to get the required information form internal repository which is useful to search required information quickly and saving a resource's effort approx. ~80%. Also, created models to identify the closest remediation from the repository which helps to make process more efficient.

Data Engineering Consultant (Data Analytics Lead) at Optum (UHG) (2015-04 – 2022-12)

• Established an Analytics & Reporting team which was responsible for execution of end-to-end projects, transformed traditional reporting into the modern reporting using visualization tools like Tableau and Power BI; Worked with 3 Data Scientists to develop predictive models for multiple use cases
• Implemented a Data science solution to Improve Program Acceptance Rate:
• This project was helpful to classify the contact that is more likely to get accepted into program by assessing the relevancy of program to customer. Increase in acceptance rate by 5% was result in reduction of claims amounts and savings in operational cost. Used Clinical data, program information level data and Clinical lab data

Sr. Analyst at Novartis Healthcare Pvt. Ltd. (2013-06 – 2015-03)

• Prepared modeling data from multiple data sources for different brands to predict the ROI for different campaigns to applying Machine Learning concepts; prepare data for Test and Controls populations to run the statistical models. Used EHR, Clinical data, Rx data, Salesforce data etc.

Associate - Projects at Cognizant Technology Solutions (2008-01 – 2013-06)

• Developed Surveys for Primary research and developed reports to analyze the sales in different geographical locations and to track the acquisition, activation and spend related information. Pulled the data from multiple sources and deliver as matrices and detail reports in Excel & PDF formats and also updating datasets in Data Mart

EPLM – IIM Calcutta