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I’m a detail-oriented Data Analyst with hands-on project experience across forensic analytics (Deloitte), commercial insights (Quantium), and AI-driven risk modeling (Tata Group). I translate raw datasets into clear, evidence-based recommendations that inform strategic decisions, and I focus on turning uncertainty into decision-ready outputs.

In my Tata iQ work, I conducted EDA on multi-source risk datasets using GenAI tools, identifying data quality gaps across 4+ risk indicators to structure inputs for a delinquency prediction model. I also designed a no-code predictive modeling framework—defining model logic, feature inputs, and evaluation criteria—to reduce manual scoring effort. Building on that, I architected an end-to-end AI-driven collections strategy integrating agentic AI and automation, grounded in ethical AI principles and regulatory compliance.

At Quantium, I analyzed transaction datasets across multiple stores and periods in Excel and SQL to uncover customer purchasing patterns and deliver commercial recommendations to the Category Manager. At Deloitte Australia, I built an interactive Tableau dashboard to communicate key forensic analytics findings to non-technical stakeholders, replacing static slide decks with a live, filterable view. With Google Data Analytics certification and strong capabilities in SQL, R, Excel, Tableau, and reporting, I bring attention to detail, cross-functional communication, and a commitment to ethical, stakeholder-ready analytics.