Originally from India, I completed my Master's in Engineering Management at the University of Illinois Urbana-Champaign (GPA: 3.8/4.0). My path from mechanical engineering to data and business analytics was not linear — it was driven by a simple realization: the most impactful work happens when you understand the data well enough to find what others miss and build systems that help people act on it.
At Oxigen Services India I worked on SBI's consumer banking network — 5,000 payment kiosks processing $6M in daily transactions. I identified an active AML structuring scheme, built fraud detection models improving accuracy from 60% to 84%, and recovered $300K through systematic exception analysis under RBI and PMLA frameworks — the Indian equivalent of BSA/AML compliance in the US. That experience shaped how I think about data, risk, and operational systems. It also taught me that the real skill is not just finding the problem — it is building something that keeps finding it after you leave the room.
Today my work spans fraud analytics, project management, marketing communications, and data platform development. At UIUC's Data Science Research Services I manage digital projects across 10+ teams using Asana, design brand-consistent marketing materials using Figma, and own the product strategy for an AI hiring platform serving 500+ users. I have also spent 1.5 years as a Teaching Assistant for iMBA courses including Project Management and Digital Marketing Analytics. Whether I am running SQL audits on 1,500 weekly transaction anomalies, managing a project schedule in Asana, or presenting KPI dashboards to a C-suite audience — I own the problem from discovery to delivery.
Project Management · Marketing Communications · Fraud & Financial Crimes · AML/BSA Compliance · AI & Data Platforms · Risk & Financial Modeling · Supply Chain & Operations
When I am not buried in transaction logs or project workflows, you will find me playing chess (rated 1800, always looking for a match), diving into conversations about historical events and mythologies, or unwinding on the dance floor. I am also building Talk Palette, an Instagram page about living an intentional, simplified life. I believe curiosity outside of work makes you sharper inside of it.
Python (LightGBM, XGBoost, SHAP, Scikit-learn, Pandas), SQL (PostgreSQL, SQL Server, DuckDB), Snowflake, PowerBI (DAX), Tableau, Alteryx, Streamlit, AWS, Salesforce (Service Cloud, Dashboards, Case Management)
Asana, Agile (Scrum), Waterfall, SDLC, Jira, Confluence, Visio, Sprint Planning, Deadline Tracking, Vendor Coordination, Budget Management, Stakeholder Management
Figma, Marketing Strategy, Brand Management, Digital Marketing Analytics, Marketing Mix, Content Creation, Google Drive, MS Teams, Zoom, MS PowerPoint
Statistical Model Building, Hypothesis Testing, Feature Engineering, Isolation Forest, SHAP Explainability, LLM Integration, Threshold Tuning, Model Benchmarking
Fraud Detection Modeling, AML/BSA Compliance, Transaction Monitoring, Exception Analysis, Anomaly Detection, Root Cause Analysis, Regulatory Reporting, Audit Trail Management
CAPM — In Progress (PMI) · CFE — In Progress (ACFE) · Six Sigma Green Belt (Ernst & Young) · Google Advanced Data Analytics Professional · AWS Cloud Practitioner
Credit Risk Modeling · Fraud Detection · AI Risk Narratives
End-to-end financial risk intelligence pipeline built on Capital One's PersonaLedger dataset — 30M transactions across 144K users. Combines LightGBM credit risk modeling, Isolation Forest fraud detection, SHAP explainability, and LLM-generated executive risk narratives for 332 high-risk customers. Flags critical-risk customers with $3.4M in at-risk exposure across 5.6M test transactions.
End-to-end inventory management platform for retail supply chain optimization. Combines multi-model demand forecasting, K-Means SKU clustering, a 6-type exception alert engine, and scenario modeling — built on 500+ SKUs and ~920K transactional records.
Credit risk evaluation using FICO methodology. Calculates customer credit scores and segments profiles into risk categories for data-driven financial decision-making.
Insurance operations teams often struggle to decide where to start with automation. TriageIQ removes the guesswork — score 15 common brokerage workflows across 9 business dimensions and instantly see which are worth automating now, which need standardizing first, and which to skip. Built for ops leaders, not developers.
Automated communication pipeline built with Python Flask and Tableau Actions. Clicking a student's NetID triggers an email via Outlook SMTP — bridging dashboards with real-world workflows.
End-to-end CLTV analysis exploring acquisition costs, conversion rates, revenue, ROI, and lifetime value across marketing channels. Rich visualizations surface actionable channel-level insights.
Interactive Tableau dashboard for sales performance and customer analytics. Features KPIs, trend analysis, and customer segmentation — designed for executives and sales managers to drive data-driven decisions.
Workforce analytics dashboard providing insights into demographics, hiring trends, salary analysis, and employee records. Enables data-driven people decisions for HR teams and hiring managers.
I love meeting fellow analysts, project managers, fraud professionals, and builders. I am open to Fraud Analytics, Financial Crimes Analytics, Risk Reporting, Data & Business Analyst, Project Management, Marketing Communications, Strategy & Operations, and Biz Ops roles. Open to relocate anywhere in the US. Let's connect.