Professional Summary

Strategic Data & AI Leader | Portfolio & Program Management | Trusted Advisor to Executive Leadership

Mission-driven data and AI leader with a track record of turning complex challenges into measurable impact across financial services, higher education, healthcare, and workforce. Today, at Fiserv, I lead program and portfolio management for a major data-product line coordinating planning, capacity, and delivery for a ~$75M portfolio across a ~120-person organization spanning data science, analytics, and engineering, and partnering with senior leadership up to the SVP level.

Earlier, I conceived and launched uHoo Analytics, an AI-powered platform adopted by 500+ faculty and recognized with the 2024 Platinum EdTech Award, transforming how an institution acts on student success, accreditation, and academic outcomes. Trusted by Provosts, Presidents, and C-suite leaders, I have delivered the executive dashboards, predictive models, and decision frameworks that shaped multimillion-dollar decisions, improved outcomes, and built lasting confidence in data-driven strategy.

Known for turning ambiguity into action, I lead with rigor, resilience, and the ability to build consensus across teams that don't always agree bridging technical depth with executive vision. I thrive at the intersection of emerging technology and human-centered impact, ensuring every solution is ethical, inclusive, and built to last.

Context/Challenge: Data Commerce Solutions' highest-revenue data-product line spanned three technical organizations data science, analytics, and engineering plus product and sales, with no unified way to plan, prioritize, or fund the work. Capacity was overcommitted, dependencies went unmanaged, leadership lacked a clear line of sight into spend versus outcomes, and long deal-and-delivery cycles were putting committed client revenue at risk. The division needed someone to turn enterprise strategy into an executable, resourced portfolio and to be trusted by leadership to make the calls.

Solution/Achievements:

• Built and now own the planning and budgeting system that converts strategy into an executable roadmap across a ~120-person, three-discipline organization, directing a ~$75M annual delivery portfolio.
• Designed the division's prioritization framework the "optimal investment mix" that directs constrained budget and engineering/science capacity toward the highest-return initiatives while protecting committed client deliveries.
• Established the performance-management system of goals, milestones, and progress tracking that leadership uses to steer spend and outcomes, replacing fragmented spreadsheets with a unified operating model.
• Lead annual and quarterly planning, executive readouts, and cross-organizational resource allocation, surfacing and resolving the dependencies and conflicts that arise when teams compete for the same capacity.
• Serve as a trusted advisor to senior leadership up to the SVP level, translating complex technical, budget, and resourcing tradeoffs into clear, decision-ready frameworks.
• Provide hands-on technical guidance to delivery teams, drawing on a prior career as a data scientist, keeping strategy and execution connected.

Impact:

• Gave leadership, for the first time, a single, reliable view of how a ~$75M portfolio is invested and where it stands against goals enabling faster, evidence-based reallocation decisions.
• Improved delivery predictability and protected committed client revenue by making capacity tradeoffs and dependencies visible before they became risks.
• Established a repeatable planning-and-prioritization discipline now relied on across the division's product portfolio.
• Strengthened cross-team alignment and trust by building consensus across organizations with competing priorities.

Growth as a Leader: This role moved me from leading analytics work to leading the strategy and investment decisions behind it. I learned to operate at the altitude where the question isn't "can we build it" but "should we, now, with these resources, against everything else competing for them" and to make those calls transparently enough that teams trust the outcome even when it isn't the one they wanted. Leading without direct authority over every team taught me that influence, clarity, and consensus are the real currency of enterprise leadership.

Context/Challenge:KSU lacked a unified system to track student success, faculty engagement, and accreditation metrics. Faculty were frustrated by fragmented data, the Provost needed transparent KPIs for decision-making, and accreditation bodies (SACSCOC) required evidence of continuous improvement. Trust in data was low.

Solution/Achievements:

• Designed and launched uHoo Analytics, a campus-wide platform powered by Azure Synapse + Power BI, integrating LMS, advising, and curriculum data.
• Grew adoption to 500+ faculty across 13 colleges, making it the university’s most widely adopted faculty-facing analytics tool.
• Created predictive models that flagged at-risk students by analyzing course performance, advising engagement, and historical DFWI rates.
• Delivered monthly executive dashboards directly to the Provost and President, shaping decisions around retention, budget allocation, and faculty development.
• Built reporting frameworks aligned with SACSCOC accreditation standards, ensuring readiness for audits and reviews.
• Chaired the AI Steering Committee, writing ethical AI policy guidelines and performing readiness assessments.
• Ran workshops to train faculty and staff, building a culture of evidence-based decision-making and breaking down distrust in analytics.

Impact:

• Platform won the 2024 Platinum EdTech Award, validating its national significance.
• Improved retention by providing faculty early intervention insights on struggling students.
• Reduced accreditation stress by producing standardized, repeatable reporting templates.
• Strengthened faculty engagement: survey feedback showed 35% increase in confidence in using data to guide instruction.

Growth as a Leader:I learned to lead through coalition-building. Success wasn’t just technical—it came from building trust with skeptical faculty, bridging silos between IT, HR, advising, and academics, and showing empathy when change felt overwhelming. This role taught me that leadership in data science is as much about storytelling and trust as it is about algorithms.

Context/Challenge:
MagMutual, one of the largest healthcare liability insurers, faced rising physician liability claims and needed a way to predict risk before it became unmanageable.

Solution/Achievements:

• Built ML models using structured and unstructured claims data to classify severity and spot high-risk patterns.
• Partnered with clinicians and legal teams to ensure models were interpretable and compliant with regulatory requirements.
• Designed early-warning risk dashboards for executives to monitor emerging liability clusters.
• Conducted workshops with underwriters and actuaries to integrate AI findings into safety protocols.

Impact:

• Models directly informed safety policy changes, reducing exposure to liability.
• Strengthened MagMutual’s reputation as a forward-thinking insurer using AI.
• Improved patient outcomes by influencing adoption of preventive measures.

Growth as a Leader:
This role taught me how to build responsibly in regulated environments. I had to balance innovation with transparency, and I learned the importance of explaining AI outputs in plain language to clinicians and lawyers.

Context/Challenge:
As the world’s largest aluminum recycler, Novelis was struggling with workforce retention and training ROI across global plants.

Solution/Achievements:

• Built HR data models that tracked attrition drivers, training effectiveness, and employee performance.
• Designed executive dashboards that revealed geographic and role-specific retention challenges.
• Identified root causes of turnover by integrating survey data, HRIS, and performance metrics.
• Proposed targeted interventions for high-turnover regions.

Impact:

• Leadership adopted retention strategies that saved millions in training and rehiring costs.
• HR gained evidence-based visibility into workforce development ROI.
• Improved overall employee engagement by connecting analytics to real human outcomes.

Growth as a Leader:
I learned how to influence global executives with data storytelling and gained experience in aligning analytics with workforce strategy. It was my first exposure to leading global-scale change through evidence.

Context/Challenge:
Equifax needed to modernize its fraud detection and credit scoring models in the face of increasing fraud sophistication.

Solution/Achievements:

• Built deep learning architectures to improve fraud detection accuracy.
• Developed ML models for credit scoring with scalable big data pipelines.
• Collaborated across data engineering, product, and compliance teams to integrate new methods.
• Authored documentation that shaped Equifax’s approach to next-gen modeling.

Impact:

• Improved fraud detection performance, directly reducing financial losses.
• Helped evolve identity resolution and customer authentication pipelines.
• Positioned Equifax to stay competitive in the rapidly shifting credit/fraud space.

Growth as a Leader:
Here, I learned enterprise-scale AI productization—balancing speed, compliance, and innovation. It was a crash course in building models that matter at scale.

Context/Challenge:
As a graduate student, I saw that retention and international student support were fragmented and under-researched.

Solution/Achievements:

• Directed multi-year applied research on retention, survey design, and student success analytics.
• Founded the International Peer Leader Program, improving retention for international students through mentorship.
• Elected President of the Graduate Student Association, representing 5,000+ students, advocating for funding, and influencing policy with the Board of Regents.
• Supported computer science teaching (C++, Data Structures), mentoring undergraduates.

Impact:

• Improved international student retention rates measurably.
• Delivered data-driven insights that shaped university policy.
• Built leadership visibility at institutional and state levels.

Growth as a Leader:
This role taught me how to advocate for diverse groups, scale initiatives from idea to impact, and balance research with leadership responsibilities. It laid the foundation for everything I do now.

• 2017-2027 (ABD)  Ph.D. in Analytics and Data Science, Kennesaw State University, USA
• 2015-2017  Master of Science in Computer Science, Kennesaw State University, USA 
• 2010-2015  Bachelor of Technology in Computer Science & Engineering,   Jawaharlal Nehru Technological University, India

I’m a mission-driven data and AI strategist who builds inclusive, human-centered systems that improve lives—especially in education, workforce, and healthcare.

My brand is rooted in turning pain into purpose. Growing up gay in a society that didn’t accept me taught me empathy and resilience. That empathy now guides how I build products, lead teams, and collaborate with stakeholders—especially when trust is low or systems feel broken.

Technically, I design scalable analytics and AI solutions that help people make better decisions. Personally, I lead with vulnerability and transparency to build trust where it didn’t exist, my work bridges the technical and human.

At the core of my brand is a belief: technology should never leave people behind.